Cloud migrations often fail or require significant rework because important risks are discovered too late. Hidden dependencies, incompatible workloads, an unprepared target environment, unrealistic migration waves, incomplete testing, data-cutover problems and weak rollback planning can all turn a manageable move into a production incident.
The safest approach is to identify uncertainty before cutover, validate each workload against its target environment, migrate in manageable waves, and define clear acceptance and rollback criteria before production traffic moves.
What Does “Cloud Migration Failure” Actually Mean?
A cloud migration does not have to collapse completely to be unsuccessful. Failure can take several forms. A cutover might be abandoned and reversed, an application might move but no longer meet its functional or performance requirements, or the migration might technically complete while leaving serious operational problems that require immediate rework.
For example, an application could start normally in its new cloud environment while a reporting service remains on-premises. If the two components communicate frequently across a connection with higher latency, the reports may become too slow for their intended use even though both systems remain individually available.
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It helps to distinguish four outcomes. A migration blocker prevents a planned workload from moving. A cutover failure prevents the new environment from taking over production successfully. A post-migration defect appears after the workload has moved. Strategic underperformance occurs when the migration technically works but does not deliver the wider business result that justified the project.
This article focuses mainly on the first three because they are closely tied to migration planning, workload preparation and execution. Broader questions about whether cloud transformation achieved its business goals belong in the surrounding digital-transformation strategy.
Failure Usually Starts Before Cutover
Cutover is often where a migration problem becomes visible, but the underlying mistake may have happened weeks earlier. Cloud migration normally moves through discovery, assessment, target design, wave planning, workload preparation, testing, cutover, validation and ongoing operation.
Google Cloud’s migration-planning guidance places workload discovery, dependency mapping, migration-strategy selection and foundation design before migration-wave planning. It also recommends running migration risk assessment alongside continuing discovery so workload-specific risks can refine later decisions.
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AWS follows the same general pattern. Its portfolio analysis and migration-planning guidance calls for a high-fidelity inventory, dependency information, a migration strategy for each application, platform readiness and a high-confidence migration-wave plan.
This lifecycle view matters because many apparent migration failures are really assessment or preparation failures that become visible only when production traffic is involved.
Where Cloud Migration Risks Usually Enter the Lifecycle
The same production symptom can originate at different stages. This table shows where several common problems are introduced and the control that should exist before the migration advances.
Common cloud migration risks by lifecycle stage
Migration stage
Typical failure
What exposes it
Risk-reduction control
Discovery and assessment
Applications, infrastructure or dependencies are missing from the migration plan.
A required database, service, identity system or integration stops working after part of the workload moves.
Maintain a verified application inventory and dependency map using discovery data plus application-owner review.
Target design
The cloud environment cannot meet workload networking, identity, security, availability or performance requirements.
The workload deploys but cannot operate safely or meet its required service levels.
Validate workload requirements against the target architecture before scheduling production migration.
Wave planning
Dependent or high-risk workloads are sequenced poorly or too much work is grouped into one wave.
Migration teams exceed capacity, dependencies are split, or cutover windows become unrealistic.
Group related systems, consider business calendars and increase complexity gradually across waves.
Preparation and testing
Compatibility problems or missing integrations are not discovered before production.
Tests pass in an incomplete environment but fail during real traffic or business workflows.
Use production-representative test environments and resolve compatibility blockers before cutover.
Cutover
Data, routing or rollback steps are incomplete or poorly coordinated.
Users reach inconsistent systems, recent transactions are missing or rollback becomes difficult.
Define final synchronization, routing, acceptance criteria, decision ownership and rollback procedures in advance.
Post-migration operation
The team declares success before verifying real-world workload behavior.
Performance, integrations, scheduled jobs, monitoring or support gaps appear after go-live.
Run production validation, monitor the stabilization period and resolve issues before closing the migration wave.
The table is not a ranking. A weakness early in the lifecycle can create several downstream symptoms, and multiple controls may be needed for the same workload.
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Incomplete Inventory and Hidden Dependencies
You cannot safely sequence systems you do not fully understand. A workload may appear to consist of one application server and one database while actually depending on identity services, file shares, third-party application programming interfaces (APIs), batch jobs, monitoring systems, scheduled tasks and other applications.
AWS describes high-confidence dependency data as an important input to migration-wave planning because both technical and nontechnical relationships affect how systems should be grouped. Its wave-planning guidance includes application dependencies, infrastructure dependencies and operational considerations among the inputs used to form migration waves.
Consider an application that makes frequent database calls. Moving the application while leaving a latency-sensitive database behind can make the application appear slow or unreliable even though both components remain individually healthy. A shared database creates another complication because several applications may have to move together or remain temporarily connected across environments.
Discovery therefore needs more than a spreadsheet compiled once at the beginning. Automated discovery can provide communication and infrastructure data, but application owners are still important because technical telemetry may not reveal monthly batch jobs, business-calendar restrictions or integrations that run infrequently.
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Google’s migration risk guidance recommends continuing discovery and assessment during wave planning so new workload-specific information can refine scope, priorities and risk mitigation.
Choosing the Wrong Migration Strategy for a Workload
Another failure pattern is applying the same migration method to every application. A workload that can be moved largely unchanged has different requirements from one that depends on unsupported software, requires substantial architecture changes or is better replaced with another service.
Rehosting, often called lift-and-shift, is not inherently a bad strategy. It can be appropriate when the objective is to move with minimal application change. The problem arises when a team chooses it without understanding compatibility, architecture or business requirements.
For example, moving a legacy application unchanged does not resolve a dependency on an unsupported operating system or a hardcoded network address. In that case, remediation, replatforming, refactoring or another workload strategy may be needed before production migration.
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Choosing the migration strategy for each workload should follow its compatibility, dependencies, business requirements and acceptable level of change.
Where teams need to distinguish the trade-offs more directly, the difference between rehost, replatform and refactor comes down largely to how much of the existing workload is preserved and how much engineering change the migration can justify.
Building the Migration Plan on Incomplete Business Requirements
A workload can be technically ready to migrate and still be scheduled at the wrong time or moved using the wrong availability assumptions. Migration planning therefore needs business information as well as infrastructure data.
Microsoft’s cloud adoption plan template for migration includes workload criticality, data sensitivity, compliance requirements, maintenance windows, business freeze periods, geographic restrictions and success metrics among the information that should inform migration planning.
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Two recovery terms are particularly useful. Recovery Time Objective (RTO) is the targeted time for restoring a service after disruption. Recovery Point Objective (RPO) describes the acceptable data-loss window, expressed as a point in time. Those requirements influence backup, replication, migration and rollback design.
A month-end finance system illustrates the problem. The software may be technically straightforward to move, but a migration window that overlaps financial close could create unacceptable disruption. Likewise, a customer-facing transaction system with a very low downtime tolerance needs a different migration approach from an internal development environment that can be unavailable for several hours.
Migrating Before the Cloud Foundation Is Ready
Workload readiness and target-environment readiness are separate questions. An application can be prepared for migration while the cloud environment still lacks the services and controls required to operate it safely.
Before production migration, teams need to know how identity, network connectivity, Domain Name System (DNS), access control, logging, monitoring, backups and operational support will work in the target environment. Larger organizations may formalize these shared capabilities as a landing zone, while smaller environments may implement a simpler foundation.
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Google’s migration-planning guidance places foundation design before migration-wave execution and lists identity and access management, networking, logging, monitoring, billing and security among the target-environment concerns that should be established and tailored to workload requirements.
Moving first and designing these controls later increases rework. An application may technically start but remain difficult to monitor, inaccessible to the correct users or connected through temporary network arrangements that need to be redesigned shortly after go-live.
Compatibility Problems Discovered Too Late
“It works on-premises” does not guarantee that a workload can move unchanged. Older software may contain assumptions about operating systems, drivers, network addresses, local storage or authentication that do not fit the target environment.
Microsoft’s current workload preparation guidance identifies issues including unsupported operating system versions, legacy network drivers, local file input/output dependencies, hardcoded IP addresses and hardcoded user accounts as compatibility problems that should be resolved before production deployment.
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The important lesson is not that every application must become cloud-native. Compatibility needs to be verified rather than assumed. A stable legacy application may still be suitable for cloud virtual machines if its operating system, networking, storage and supporting software can operate correctly and remain supportable.
Problems should be remediated and retested before the production move. Discovering a blocker while users are waiting for cutover completion leaves the team with fewer safe options and greater pressure to accept temporary fixes.
Security and Governance Are Added After the Move
Security becomes harder to retrofit once workloads have already been deployed around weak assumptions. Identity, access control, data protection, network design, logging and incident response should therefore influence migration planning rather than becoming a cleanup project after cutover.
Microsoft’s secure cloud adoption guidance recommends integrating security considerations into every phase of cloud adoption and includes confidentiality, integrity, availability, incident preparedness and landing-zone security among the areas that require planning.
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This does not mean every migration needs identical controls. Requirements depend on the workload, data, organization and applicable obligations. A public marketing site and a financial transaction system should not receive identical risk treatment simply because both are moving to cloud infrastructure.
Governance matters for the same reason. Teams need clear rules about who can provision resources, who approves access, how activity is logged, how exceptions are handled and who owns security decisions after migration.
Migration Waves Are Too Large or Poorly Sequenced
A migration wave is a group of workloads moved within the same planned period. Waves make a large migration program easier to control, but poor grouping can create new risk.
AWS recommends combining prioritization, dependency information and business drivers when building waves, and its portfolio migration guidance recommends prioritizing simpler, noncritical applications in early waves while considering security, operational and platform readiness.
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Microsoft similarly recommends grouping dependent systems and using lessons from completed waves to refine later planning. Its migration-wave planning guidance also emphasizes business timing, team capacity, testing, rollback procedures and success criteria.
A common mistake is moving too many critical workloads together because a calendar deadline is approaching. That concentrates technical complexity and can exceed the capacity of migration, application, security and support teams at exactly the point where fast decisions are needed.
Waves should be revised as the organization learns. A dependency discovered during one migration may change the grouping or timing of several later workloads.
Testing Does Not Resemble Production
A test environment can produce reassuring results while still failing to represent the conditions that matter in production. Missing integrations, different identity configuration, unrealistic traffic or configuration drift can hide defects until cutover.
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Microsoft’s workload-preparation guidance says test environments should contain the required dependencies, configurations and integrations because missing components can produce false positives or leave problems undetected. Its environment guidance describes configuration drift as discrepancies between environments and recommends keeping staging as close to production as practical.
Testing should cover more than whether the application opens. Functional tests confirm expected application behavior. Integration testing verifies communication with databases, identity systems and external services. Performance testing checks whether the target environment can handle realistic demand. User acceptance testing verifies important business workflows from the user’s perspective.
Microsoft’s pre-migration validation guidance specifically calls for functional, integration, regression, performance and stakeholder acceptance testing before production deployment.
For example, a migrated order-processing application might pass a basic login test but fail when it attempts to call a payment integration, create a scheduled export or process peak transaction volume.
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The practical standard is not perfect duplication of production. It is enough similarity that testing exercises the dependencies, configuration and load characteristics most likely to affect production behavior.
Data Synchronization and Cutover Are Underplanned
Moving compute is only one part of migrating a stateful application. Databases, files and transaction data may continue changing while the target environment is being prepared, so teams need a defined point at which data is synchronized and production traffic switches.
AWS’s cutover guidance describes a sequence that can include an ingestion freeze, final backup, final data synchronization, routing changes, testing and validation before the migration is considered complete.
This becomes especially important when users can create new data immediately after cutover. Once transactions exist only in the new environment, rolling back to an older source environment can discard or conflict with those changes unless a reconciliation or replication method has been prepared.
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DNS changes, load-balancer changes and other routing steps also need to be coordinated with application readiness. Redirecting users too early can expose an environment that has not completed data synchronization or acceptance testing. Maintaining two writable environments without an intentional synchronization design can introduce a different consistency problem.
A cloud migration cutover checklist can turn acceptance criteria, data synchronization, rollback triggers and post-cutover validation into explicit go-live controls.
The Rollback Plan Exists Only on Paper
A useful rollback plan answers two questions before cutover begins: when should the team stop? and how will service be restored?
AWS recommends defining rollback checkpoints, a strategy for handling the rollback and its data, and a named contact who decides whether to fix forward or return to the previous environment. Its cutover guidance also distinguishes rollback before new data is created from rollback after the cloud system has accepted new transactions.
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That distinction matters. Before new writes occur, rollback may involve restarting the source environment and reversing routing changes. After new transactions have been recorded in the cloud environment, the source data may be stale and the team needs a way to reconcile, replicate or restore the newer data.
A practical rollback plan therefore includes the trigger, decision owner, technical procedure, data-handling method, expected restoration time and validation procedure. Microsoft also recommends documenting rollback triggers, backup and restoration procedures, recovery validation steps, and regularly testing those procedures before they are needed.
Tested backup and recovery planning supports this process, but a backup by itself is not a complete rollback strategy. Traffic routing, application state, data consistency and acceptance checks still have to be handled.
Skills and Ownership Gaps Appear During Execution
Cloud migration is not only a tooling problem. Someone must understand the application, someone must own the platform, someone must make security decisions, and someone must decide whether production acceptance criteria have been met.
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Microsoft’s migration-plan template explicitly includes operating-model responsibilities, workload ownership and cloud training because teams need clear accountability before workloads move. The planning framework also recommends documenting platform and workload responsibilities rather than assigning them after deployment.
A common failure pattern is that the migration team can move the workload, but nobody is clearly responsible for monitoring it afterward. Another is that a business owner is unavailable during cutover, so technical staff cannot confirm whether an important workflow is functioning correctly.
For each migration wave, identify the workload owner, platform owner, security contact, migration lead, business acceptance owner and escalation path. Small organizations may combine several roles, but the responsibilities still need to be explicit.
The Team Declares Success at Cutover
Routing production traffic to the new environment is a milestone, not the end of the migration. Workloads need post-cutover validation under real operating conditions before the wave is considered complete.
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Validation should confirm user access, important business transactions, integrations, scheduled jobs, monitoring, performance, backup behavior and error rates. The operations team also needs updated documentation and a clear support path.
AWS’s migration-planning guidance treats test, cutover, validation, wave closure, lessons learned and resolution of post-migration issues as parts of the migration-wave lifecycle rather than treating cutover as the finish line.
A stabilization period is useful because some issues appear only under real traffic or after scheduled processes run. An overnight batch job, for example, may reveal a missing file path several hours after daytime users have successfully tested the application.
How to Reduce Cloud Migration Risk Before Go-Live
Before approving production cutover, confirm that the major uncertainties identified during planning have been converted into observable readiness conditions. These checks are parallel gates rather than a substitute for a detailed cutover runbook.
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Verify the result
The workload inventory and dependency map have been validated against current discovery data and application-owner knowledge.
A migration strategy has been assigned to the workload and its major components, with known compatibility blockers resolved or explicitly accepted.
The target environment has the required identity, networking, security, logging, monitoring, backup and operational controls.
The test environment includes the dependencies, integrations and configuration needed to represent important production behavior.
Functional, integration, performance and business-acceptance results meet the migration’s documented success criteria.
The final data synchronization and traffic-routing process has been rehearsed or otherwise validated for the workload.
Rollback triggers, decision ownership, technical steps and data-reconciliation requirements are documented and understood by the cutover team.
Application, infrastructure, security and business owners are available for the planned cutover and escalation window.
Post-cutover monitoring, operational ownership and stabilization support are ready before production traffic moves.
No checklist can remove every migration risk. Its value is that unresolved assumptions become visible before time pressure and production impact make them harder to address.
Conclusion
Cloud migrations become safer when teams discover uncertainty early rather than trying to compensate for it during cutover. Complete workload and dependency information, realistic testing, controlled migration waves, a prepared target environment and a usable rollback strategy give teams more options when something behaves differently from the plan.
The most important shift is to treat migration as a lifecycle rather than a transfer event. Cutover is only one stage. The quality of discovery, assessment, preparation and validation around it largely determines how much unresolved risk reaches production.
Defense and venture capital used to rarely overlap, but that’s no longer the case. Defense tech VC dealmaking set a record in Q1 2026, and new VC firms have emerged around the world to invest solely in defense startups.
One of these is two-year-old Protego Ventures, which presents itself as the first and largest dedicated defense tech VC in Israel. Led notably by two women, Lital Leshem and Lee Moser, it has just completed the final close of its debut fund with $125 million in capital commitments, TechCrunch learned exclusively.
This fund size is enabling Protego to invest between $5 million and $50 million per company, with a focus on startups “addressing the critical defense and security needs of Israel and the global community,” according to its website.
These include the likes of drone maker XTEND, its first portfolio company, which went public on the NYSE earlier this month. That’s also why Protego stopped short of its $150 million target: a smaller fund magnifies the impact of a single big win on overall returns, and with XTEND now looking like a potential “fund maker” — a single investment capable of returning the whole fund — raising more capital would only dilute that upside among a larger pool of investors. “Nobody wants to share the pie,” Leshem said.
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Ares Management is one of Protego’s biggest backers. The investment firm suggested that Leshem and Moser join forces and start Protego in the aftermath of the October 7, 2023, Hamas attack on Israel, with the conviction that new technologies would be key to boosting Israel’s defense capabilities in the face of new threats, Leshem said.
With a $30 million investment as a limited partner, Ares gave Protego the support it needed to start investing right away, Leshem said. Besides XTEND, its portfolio also includes startups such as ASIO, which develops situational awareness systems and has partnered with Anduril.
Leshem says the reception in defense circles has been strong. “On the military side, there is a lot of respect, and people are coming — even under the radar — to talk to us, to learn from us, to train with us, and for sure get our technology and innovation.”
Still, the Israeli market is easier to navigate for insiders, and Protego’s two founders are leaning into their networks. Moser, a seasoned venture capitalist, will remain a managing partner at the generalist VC firm AnD Ventures. As for Leshem, who co-founded a startup that was acquired for $625 million in 2025, she also brings 11 years of experience in the military and intelligence field to their approach.
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“Everything changed on October 7,” Leshem told TechCrunch. She was deployed, while pregnant, as a reservist on the day of the attacks. “And basically until the delivery room, I was there, witnessing and getting the first-row seat to how the battlefield acted differently from what I knew in the past decade.”
Protego won’t have the field to itself for long. Israeli authorities have taken notice of the same shift, awarding VC firms Adir Capital and Sling Capital about $33 million in state guarantees to invest in military and dual-use technologies, with other funds also raising capital for similar bets. (Leshem said Protego was too far along in its own fundraising to take part in the government’s tender.)
Protego, meanwhile, is already planning its next move: a second fund in the first quarter of 2027, backed by Israeli institutional investors and one large U.S. commitment Leshem has already secured, with a broader scope that includes early-growth American defense-tech companies.
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Washington Gov. Bob Ferguson kicks off the Washington Space Council, surrounded by the council’s members and 10-year-old Sebastian Yu. (GeekWire Photo / Alan Boyle)
Washington Gov. Bob Ferguson has created a public-private council to elevate the Evergreen State’s profile as regional clusters compete for primacy in America’s space industry.
The 23-member Washington Space Council was introduced tonight at the Museum of Flight during a kickoff event for Seattle Space Week, a celebration organized by Space Northwest.
“The council will help keep us competitive by comparing Washington with other leading states in the industry and identifying ways we can continue to improve and compete,” Ferguson said.
Washington state already ranks as one of the nation’s space industry hotspots. “We’re proud to have a cluster of more than 90 space companies employing more than 13,000 workers, generating over $4 billion in annual economic activity and $1.6 billion in annual payroll,” Ferguson said.
But Andy Lapsa, co-founder and CEO of Kent, Wash.-based Stoke Space, told tonight’s crowd that several other regions are competing with the Pacific Northwest for space-related investments. “States like Florida and Texas and Colorado want this industry, and they want it bad,” he said. “They compete for it every day. Washington has every advantage it needs to lead them all, and the window to use those advantages is open right now.”
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Boeing has historically been the state’s leading venture in aerospace, but when you focus on ventures that concentrate strictly on space, Blue Origin is high on the list. Seattle is particularly strong in the satellite sector: More than half of the world’s satellites are built in the Seattle area, thanks to SpaceX’s Starlink facilities in Redmond and Woodinville, plus Amazon Leo’s factory in Kirkland, BlackSky’s production plant in Tukwila and Xplore’s operation in Bellevue.
Gravitics, Interlune, Portal Space Systems, Starcloud and Starfish Space are among other space ventures represented on the Washington Space Council. The list also includes elected officials, union leaders, educators and investors, plus representatives from space-related tech companies and Pacific Northwest National Laboratory.
The 23-member Washington State Council includes representatives from government, academia and the space industry. Click on the image to get the full list from the Washington State Department of Commerce.
Ferguson said the council will “identify barriers for the industry and find opportunities for growth.”
“That includes, by the way, workforce development, infrastructure and much more,” he said. “And the council will look for ways we might be able to develop Washington-based commercial launch capabilities. That would be a very exciting addition to what we’re doing right here in Washington.”
Ferguson brought a member of the audience, 10-year-old Sebastian Yu, to the stage when he signed the executive order that officially created the council. After the signing, the governor handed the pen to Yu.
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“Your assignment, Sebastian, is that when we do that first launch, you have to save this pen and bring it with you to the first launch,” Ferguson said. “Take care of this pen, OK? I’m going to expect to see it again someday.”
Notes from the kickoff:
Space Northwest presented three awards to recognize contributions to the region’s space industry. The Shooting Star award for municipal support went to the city of Kent, Wash. Portal Space Systems won the Rising Star award for emerging space companies, and SpaceX won the North Star Award for large space companies.
Kent Mayor Dana Ralph noted that her city’s connection to the space industry goes back to Boeing’s work on the lunar rovers for NASA’s Apollo moon missions in the 1970s, while acknowledging that Kent can’t rest on its laurels. “Our job is to make it possible for companies to build and grow and hire. That means reinvesting in the basics: roads, great mobility, water, sewer, plentiful and easily accessible energy and industrial land,” she said.
Mehran Mesbahi, professor and chair of the University of Washington’s Department of Aeronautics and Astronautics, highlighted efforts to boost careers in the space industry. “We have Husky Satellite Lab, a group of energized students at UW, and we’re going to create a certificate program around space systems going forward,” he said.
Seattle Space Week continues on Tuesday with the Space Northwest Symposium at the Federal Way Performing Arts & Event Center.
Among the many joys of having a cat is the daily battle with the mess they leave behind. No matter what you try, finding litter and pet hair on furniture or in your bed is inevitable — either they track it in, or you do. If you’re a pet parent like me, this means searching for additional bits of litter and stray hairs that find their way into places you really don’t want them, including the bed. Short of pulling the sheets off entirely, few fixes exist.
I took a chance and tested the SandBar Roller, a $30 dual-roll lint roller, to see if it can make it easier to keep stray hair and litter at bay. I also put it through the paces for other lint-roller tasks like dusting and cleaning floors. Here’s how it fared.
How SandBar Roller differs from other lint rollers
The SandBar Roller Starter Kit I tested included the roller head, an extendable handle and two preinstalled lint rolls.John Carlsen/CNET
The SandBar Roller’s appeal lies in its two large lint rollers instead of one. While the idea doesn’t seem like much of a departure from a typical large lint roller, I couldn’t find any other dual-roller designs intended for use between bedsheets like SandBar. By arranging the rollers in this way, SandBar can clean the top and bottom sheets simultaneously without getting stuck.
The Best Handheld Vacuums, Tested by CNET
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While SandBar markets its proprietary lint rolls as stronger than normal rolls, they’re not much different from what you’ll find on the extra-large pet hair version of the Scotch-Brite lint roller. Both are 8 inches wide, with an inner diameter of 1.5 inches. Much to SandBar’s credit, its six-pack of refill rolls is just $20, which is very competitive with other lint roll refills I found on Amazon, with the optional subscription price dropping to just $16 for each one-, two- or three-month delivery.
Testing the SandBar Roller
The extendable handle is very practical.John Carlsen/CNET
Ostensibly, this design targets coastal homes, where sand gets everywhere — hence the SandBar name. While I don’t live on the coast, I’ve experienced sand in my bed while traveling, or after day trips to the desert, and cat litter is a near-daily occurrence. With that in mind, I conducted a series of informal tests to see how the SandBar Roller holds up.
Upon putting SandBar between the sheets, I noticed it moved fairly smoothly, at least until it snagged on some sheets that were too loose. It didn’t jam, but that means it works better for beds with the sheet firmly tucked at the foot — something I don’t do for various sleep-friendly reasons. Still, it worked well after tightening the sheets a bit, even snagging a few cat hairs and litter fragments. It’s a nice alternative to washing the sheets as frequently as I have to now.
I like the stickiness of the rolls, which is satisfyingly tacky without leaving residue or making it difficult to pull off used strips.John Carlsen/CNET
The SandBar removed cat fur from hard-to-reach places
Next, I wanted to see how it handled cleaning smart window shades and curtains, which often collect fur as my cat patrols windows a few times a day. It was a little more awkward, but taking the handle off proved effective, and the sticky roller collected a substantial amount of fur. I had to peel off multiple sheets because of the amount of fur, but it took only a few passes to clean the curtain. The SandBar Roller was very useful on furniture and pet beds, but I noticed that being too aggressive can occasionally dislodge a roll.
The SandBar Roller left a fairly clean surface when I dusted off a TV cabinet and soundbar. Still, I wouldn’t trade it out for the duster and handheld vacuum I usually use. Likewise, it did well on the linoleum floor and carpet near my cat’s litter box, but still I prefer the cleaner result I get from vacuuming.
Should you buy the SandBar Roller?
The specialized design does its job well, but is probably too niche for people who aren’t pet parents or near vast swathes of sand.John Carlsen/CNET
At $30, the SandBar Roller is unlikely to break anyone’s budget, especially when you can find similarly large bed lint rollers for the same price. In that context alone, including the cost of refill rolls, it’s probably as good as any other option. Still, the dual-roll design’s ability to get between sheets is a compelling reason to consider the SandBar Roller over the competition. The design suits households that typically deal with a lot of sand and litter in the beds. I could even see myself taking it camping for quick dirt cleanup in a sleeping bag.
However, I wouldn’t recommend it for short-term beach house rentals because it cuts corners — new guests expect clean sheets when they arrive. That said, making a SandBar Roller available during a guest’s visit could be worthwhile to improve their experience, as long as you leave instructions explaining what it’s for and how it works.
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If you don’t need the second roll — and mainly deal with pet hair on furniture — the ChomChom Roller doesn’t need refill rolls, making it a much better option for $25. Likewise, a handheld vacuum can do the same job with a bit more flexibility around the house — though it’s not quiet enough to use when others are sleeping. While it’s nice to have so many options, it’s always worth going with what works best for your needs and situation.
John Carlsen has more than a decade of experience testing and reviewing home tech products, with a major focus on smart home security. He earned his BS in journalism from Utah Valley University. In addition to his CNET contributions, John has written for Android Police, TWICE, Home Theater Review, SafeWise, ASecureLife and Top Ten Reviews.
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If you haven’t heard of Metal Gear, you probably haven’t played video games these last few decades. The original Metal Gear dates back to 1987 and launched on the MSX, but the real rise to fame probably started with Metal Gear Solid on the original PlayStation in 1998. What needed a hefty console in 1998 can comfortably fit on a microcontroller in 2026, though, as [David Montero Crespo] demonstrates with his port of MGS to the ESP32-S3.
[David] is — as we always are — standing on the shoulders of giants with this hack. Most specifically, the project relies entirely on the [FoxdieTeam] MGS Reversing decompliation project. Of course what one team decompiles, another can recompile, and in this case [David] chose to recompile the game for Expressif’s exceptional ESP32. It wasn’t quite as easy as just forking the repo and compiling with the ESP32 as a target though, as the blog post explains.
We won’t spoil it, but [David] did have to make some changes to account for the different quirks the MIPS processor in the PlayStation has compared to the Xtensa cores on the microcontroller. Then to make it playable, he put the ESP32-S3 module onto some perfboard with an analog stick from a drone controller, an ILI9341 LCD panel, and a resistor ladder to run the buttons for a barebones handheld.
OpenAI was gearing up to release GPT-6.1 Astra, its next AI model, with an October launch in its sights. That’s no longer happening. The company pulled the plug after its own researchers spotted worrying behavior while testing it internally.
What went wrong with GPT-6.1 Astra?
On paper, Astra-6.1 was an upgrade over the current GPT-6 Astra. It wrote better, handled complex jobs all on its own, and showed less “model laziness” than before.
OpenAI
However, in an interview with The Wall Street Journal, Saachi Jain, OpenAI’s head of safety systems, said the model slipped in two important areas. First, it sometimes misled users about what it had actually done. Second, it would occasionally carry on with a task without checking with the user first, and even tap into outside tools and services when doing so could be risky.
“For anything regarding safety and alignment, there’s a trade-off,” Jain said. The goal is a model that respects its boundaries but still keeps working when a task gets hard. Astra fell short of OpenAI’s bar, so the public launch was called off.
Why is OpenAI hitting the brakes now?
AI agents have had a messy few months. Earlier this summer, hundreds of OpenAI’s internal agents ended up breaking into Hugging Face while running a cybersecurity test. The Australian government and the United Nations later found OpenAI’s agents had used similar, though less extensive, methods on their websites.
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Andrew Neel / Unsplash
Last week, OpenAI also halted training on its most powerful models after one agent found a loophole in its internet restrictions and queried a public chatbot. OpenAI says Astra is a separate case. Lawmakers are watching, too. According to WSJ, a Senate subcommittee is holding a hearing on rogue AI agents this week, and Florida’s Attorney General has been suing OpenAI since June.
What does this mean for you?
You won’t be getting GPT-6.1 Astra anytime soon. OpenAI hopes to reuse its base model to build future GPT-6 models and is digging into what caused the problems. Personally, I’d rather wait for an AI that’s honest about its work than use one that goes off and does its own thing.
New research suggests Enceladus may be an especially promising place to search for extraterrestrial life: microbes similar to those found near Earth’s hydrothermal vents survived in lab conditions designed to mimic the Saturnian moon’s subsurface ocean. A separate study also found that material blasted from Enceladus’ plumes may naturally separate and concentrate salts, organics and potential biosignatures into individual ice grains, potentially making them easier for future spacecraft to detect.
“That is great news in the search for life,” Frank Postberg, lead author of one and co-author of the other of these new studies and professor at Freie Universitat Berlin, said in a statement. “Future spacecraft will have to analyze many individual ice particles in the plume. But if they come across one with microbial material in it, they could identify biosignatures in the particle relatively easy with already available technology.” Space.com reports: Enceladus isn’t the only place in our solar system with water — so, why is it so exciting in the search for life? Well, it has to do with the seafloor of its extensive, liquid ocean. Down deep at the bottom of this body of water, scientists think hydrothermal processes, or movement or reactions with hot water under the surface, are taking place. The plumes shooting upward from the ocean also contain trace amounts of salts and organic compounds. NASA’s Cassini spacecraft found these traces when it flew through the plumes over a decade ago. Between the hydrothermal activity and the organics and minerals in the water, this moon’s ocean has a number of aspects that could be involved in supporting life.
What’s more, using a combination of Cassini data, theoretical models and laboratory experimentation, in Postberg’s new study the team found that the plume’s water droplets blasting out into space at up to 621 miles per hour (1,000 kilometers per hour) don’t freeze as quickly as expected. Before, scientists thought the freeze would happen instantaneously once the droplets reached space, but Postberg and fellow researchers say they found the freezing would actually happen much slower.
They also found that during this freezing process, the salt, organic compounds (and maybe possible signs of life) in the water droplets separate from one another. Not only that, but the team says that as the particles are blasted out into space, they should often collide with the icy cracks of the planet’s surface. This ultimately would leave behind tiny shards of frozen droplets with individually separated out components. Essentially, it’s like the planet has organized its oceanic ingredients into tiny, frozen particle fragments. This work is described in two new studies published in the journal Science Advances here and here.
In context: Android smartphone maker Nothing has launched the Headphone (1) Pro, its new flagship audio product, which it claims combines an elevated listening experience for consumers with studio-grade production and mixing features for professionals. It succeeds last year’s Nothing Headphone (1), which TIME named one of its Best Inventions of 2025.
The biggest change in the new model is a three-driver audio system. It includes a bass dynamic driver designed to add more punch and sensitivity to low frequencies, a precision dynamic driver that adds more texture to vocals and instruments, and a new treble xMEMS driver that Nothing says delivers crisper highs.
Nothing also worked with London’s Metropolis Studios to tune the Headphone (1) Pro, with the collaboration focused on professional audio tools and soundstage characteristics.
The company also highlights an improved adaptive active noise cancellation system that uses a 10-microphone array to more accurately filter ambient noise than the first-gen model. With claimed noise reduction of up to 46 dB, Nothing is positioning the Headphone (1) Pro against premium rivals from Bose and Sony.
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Nothing says the improvement in noise reduction should be particularly noticeable in strong winds or noisy traffic. The headphones also feature redesigned ear cushions with an 8mm silicone baffle wall inside, creating a stronger sound barrier and improving the seal around the ears.
The Headphone (1) Pro supports Hi-Res wireless audio and wired playback over USB-C at up to 24-bit/192 kHz. It also offers five modes of Dynamic Spatial Audio with head tracking, along with five new custom EQ profiles. A separate Flat EQ switch is designed to give producers and creators a more neutral sound profile.
The Headphones 1 Pro is built out of aluminum and titanium to provide a durable shell while creating a premium look and feel. It also retains Nothing’s transparent design language, using shatter- and scratch-resistant 9H Panda Glass on both ear cups to reveal parts of the triple-driver architecture.
Despite the increased use of metal, Nothing has reduced the headphones’ weight to 327 grams through a redesigned internal architecture, including replacing steel arms with titanium. Other changes intended to improve comfort over longer listening sessions include a wider headband with thicker padding and softer ear cushions.
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The Headphone (1) Pro is positioned to compete with premium models such as the Sony WH-1000XM6, Bose QuietComfort Ultra, and Apple AirPods Max. It is priced at $399 and will be available beginning September 29 through Nothing’s official store at nothing.tech, Amazon, and Best Buy stores across across the US and Canada.
Ned Jenkinson of the University of Birmingham and Matthew Weightman of the University of Oxford discuss how advancements in brain research might affect how we learn and grow our skillsets.
Whether learning a new piano piece or adapting your tennis serve, acquiring physical skills depends on your brain’s ability tostrengthen and refine neural connections. Researchers are exploring whether this process can be accelerated with technology.
Scientists are particularly interested in the potential of non-invasivebrain stimulation, a group of techniques that can alter brain activity without surgery.
If these techniques can successfully enhanceneuroplasticity, the brain’s ability to reorganise and form new connections during learning, then they could be of use anywhere where performance depends on learning complex movements, from sport and music to surgery and beyond. Researchers are also seeing if these technologies could help with learning non-physical skills, such aspicking up a foreign language.
Elite sport, professional gaming and high-performance workplaces could all become targets for these enhancements if they prove effective. Brain stimulation could also have a big role to play in medicine, helping patients recover physical skills lost through injury or disease, such asstroke.
Studies suggest there’s a lot of potential here. But translating this potential into useful tech that reliably boosts learning physical skills remains a big challenge.
Stimulating findings
Research into enhancing motor learning with electric or magnetic stimulation has been gaining momentum since the turn of the millennium, with early studies garnering considerable excitement.
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In atypical experiment, participants might learn a sequence of finger movements similar to practising scales on a piano while receiving stimulation over brain regions involved in movement. Other studies have examined how stimulation could be used forbalance training or teachingsports-relatedskills orsurgical techniques.
Some of these experiments produced eye-catching results, finding that participantslearned certain movement tasks faster orretained skills for longer if they underwent brain stimulation. But other studies failed to find benefits. And in some cases, researchers struggled to replicate the success of earlier promising experiments when repeating them.
One reason for these mixed findings is that there’s no such thing as a universal ‘learning network’ in our brains. Different skills rely ondifferent combinations of areas near the surface of the brain as well as those deep within it.
Additionally, people can respond very differently to the same stimulation. Factors such as age, anatomy, genetics and even baseline skill level may influence whether stimulation is beneficial. Add to that the infinite number of ways to apply stimulation, the picture becomes murkier.
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Despite these challenges, the field continues to evolve in its quest to enhance motor learning. For instance, rather than broadly stimulating the brain, researchers are increasingly targeting specific neural circuits involved in learning.
This is partly thanks to advances inneuroimaging andcomputational modelling, which has allowed scientists to predict how electrical currents travel through a person’s brain. Newer brain stimulation technologies, such as focused ultrasound, can also now reach deep structures involved in skill acquisition.
The goal is to use these technologies not simply to increase brain activity, but to influence the right neural circuit at the right time during learning. This idea builds on a fundamental principle of neuroscience, often summarised as“neurons that fire together, wire together”. When brain cells are repeatedly activated at the same time, the connections between them become stronger.
By carefully timing stimulation tocoincide with the movements made during practice, researchers hope to reinforce the neural pathways involved in learning a new skill. In principle, this could make stimulation more reliable and more effective than current approaches, but researchers are stillfine tuning exactly how this would work.
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Motoring ahead
Important questions remain. Who would have access? Should stimulation be regulated in competitive environments such as sport? And how much evidence should be required before consumer devices are marketed to healthy users?
These questions are becoming increasingly relevant as brain stimulation moves beyond the laboratory and clinic. A number of at-home devices are now available for people to buy.Some have receivedregulatory approval, as they’re indicated for treating medical conditions such as depression. But there’s also a growing market for devices forcognitive and performance enhancement. For these uses, no regulatory approval is needed.
The technology is advancing rapidly, but evidence to support it and regulations governing it are still trying to catch up. Proper frameworks for its adoption may simply be bypassed by the ready possibility of ‘DIY’ brain stimulation.
For now, brain stimulation is unlikely to transform anyone into an overnight virtuoso or elite athlete. But as researchers develop increasingly precise ways of targeting the neural circuits that underpin learning, the prospect of enhancing human performance is shifting from science fiction towards scientific possibility.
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The challenge today is not simply learning how to influence the brain, but deciding where, when and why we should.
Ned Jenkinson is a senior lecturer in human movement sciences at the School of Sport and Exercise Sciences at the University of Birmingham. His research incorporates a range of techniques including non-invasive brain stimulation, electrophysiological recording, eye-tracking, neuroimaging and behavioural techniques. He uses these techniques to investigate how the brain controls movement and how it allows us to learn new motor skills.
Matthew Weightman is a postdoctoral researcher at the Oxford Centre for Integrative Neuroimaging in the Plasticity Group at the University of Oxford, led by Prof Heidi Johansen-Berg. He is broadly interested in the field of sensorimotor neuroscience. His current work focuses on the role of sleep to recovery after stroke. More specifically, he is interested in how we can improve sleep after a stroke, whether improved sleep in stroke patients relates to better functional recovery, and if physiological processes that occur during sleep can be enhanced post-stroke to boost consolidation.
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Keio Corporation (Keio), a major private railway operator in Japan, said its network was hit by a ransomware attack over the weekend, disrupting some of its business systems.
Following a system failure in the early hours of Saturday, the company confirmed the attack and shut down its network to prevent additional damage.
The company said it is investigating the extent of the impact and whether the attackers accessed any customer or business partner information.
Keio is a large Japanese railway operator with 85 km of track and 69 stations, as well as a separate hospitality business of 25 hotels. The company has over 2,200 employees and a reported annual revenue of about $2.6 billion.
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“In the early hours of September 26, 2026, we confirmed a ransomware attack on our group’s servers. We have reported the incident to the police and are conducting an investigation into the attack’s route and damage with the cooperation of external experts,” Keio says.
The incident appears to have affected only the hospitality side of Keio’s business, not train operations.
A separate announcement published on the company’s Keio Plaza Hotel Tokyo website is warning of possible delays on some customer-facing services.
At the time of writing, BleepingComputer could not find a ransomware group claiming the attack on Keio.
BleepingComputer has contacted the company to request more information about the incident, and we will update this post with their response once it reaches us.
Tokyo Metro has also disclosed a cyber incident over the weekend in which attackers gained unauthorized access to its systems and accessed 59,000 member email addresses.
Although both Keio and Tokyo Metro are Japanese railway operators, it is unclear if the organizations were targeted in a coordinated campaign by the same threat actor.
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Tokyo Metro is a major transit operator that runs nine subway lines covering 195 km and 180 stations, carrying an average of 7 million passengers daily.
The company said the breached systems contained only email addresses and that it has already identified and closed the security weakness the attackers used in this case.
Join Mikko Hyppönen and security leaders from the NFL, CHANEL, and Atlassian for a two-hour digital summit on what AI-speed attacks change, what defenders should stop doing, and how to validate, decide, fix, and re-validate at machine speed.
Home puts chats, delegated work, and Office documents inside one interface
Code lets non-programmers describe software and have Copilot build it
Autopilot can continue recurring work without waiting for another instruction
Microsoft has introduced a redesigned version of its Copilot AI platform which claims to combine chat, delegated work, and coding tools into a unified application experience for users.
The company says the update is meant to let individuals and organizations scale artificial intelligence across everyday tasks and long-term projects.
Three new capabilities anchor this release, including Home, Code and Autopilot, each aimed at a different kind of work.
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Home brings Chat and Cowork together
The Home tool brings together two existing modes, Chat for quick questions and Cowork for tasks users delegate entirely, under one shared starting point.
Word, Excel, and PowerPoint now operate inside this same interface, letting users draft documents, budgets, and presentations without switching applications.
In these documents, Copilot is now grounded in Fabric IQ, pulling context from more than 20 million semantic models built in Power BI.
Edits made by colleagues or by the assistant itself appear in real time, so progress stays synchronized across a shared file.
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A new plugin registry will let organizations manage Microsoft, partner and custom-built plugins from one central catalog starting this month.
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Independent developers and partners can also publish plugins once for use across multiple Copilot surfaces under the new registry arrangement.
The Code tool allows non-programmers to describe an app, tracker or dashboard in plain language and have it built automatically.
This feature runs on the same underlying technology used in GitHub Copilot and can be hosted within a company’s own systems.
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Autopilot operates without constant prompting
Autopilot, the third addition, is a persistent agent capable of completing recurring work without needing a new instruction each time.
It can run supplier reviews or similar multi-step processes, build schedules, contact stakeholders, and follow up on outstanding items independently.
Because it operates continuously in the cloud, work can continue late at night or whenever a person’s attention shifts elsewhere.
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A related feature called Today, entering private preview in October, will summarize missed messages and pending tasks across mail and chat.
Microsoft is also tying spending controls to these tools through a system it calls FinOps for AI, letting administrators track usage.
Administrators can set spending limits, approve credit requests and restrict which AI models different teams are permitted to use each month.
Everyday tasks like quick answers or first drafts run on a fixed-price subscription, while agentic features use usage-based billing.
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Code, Cowork and Autopilot all fall under this usage-based pricing model, alongside frontier models Microsoft refers to as Astra and Fable.
Home and Code are set to roll out through Microsoft’s Frontier program within weeks, and Autopilot enters private preview by month’s end.
Microsoft has not released independent data showing how widely the three features are being adopted, how accurate they are, or how much time they actually save.
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