# snapshots Published articles for snapshots. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Kubernetes 1.36 restores a lost guarantee for database backups DevFeed: [Kubernetes 1.36 restores a lost guarantee for database backups]() Original publisher: [Read original article]() Author: Shubham Pampattiwar Published: 2026-09-15T13:00:00Z Content type: news Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack](), [The New Stack]() Topics: [Kubernetes](), [PostgreSQL](), [Databases]() Tags: [backups](), [cncf](), [consistency](), [database](), [databases](), [kubernetes](), [post-contributed](), [postgresql](), [snapshots](), [sponsor-cncf](), [sponsored-post-contributed](), [stateful](), [storage]() ### AI overview The article explains how Kubernetes 1.36 restores coordinated snapshots for applications whose state spans multiple volumes, addressing inconsistent database backups caused by taking individual PersistentVolumeClaim snapshots at different times. ### Source excerpt It's 2 a.m., and you're restoring a PostgreSQL cluster from last night's backup. Its data directory lives on one PersistentVolumeClaim The post Kubernetes 1.36 restores a lost guarantee for database backups appeared first on The New Stack. ## Kubernetes Changed Block Tracking API - Beta Differences DevFeed: [Kubernetes Changed Block Tracking API - Beta Differences]() Original publisher: [Read original article]() Author: Prasad Ghangal Published: 2026-09-14T18:30:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [API](), [gRPC]() Tags: [2026](), [compatibility](), [container-image-registry](), [developer](), [documentation](), [kubernetes](), [registry](), [release](), [snapshots](), [storage](), [streaming](), [update]() ### AI overview This Kubernetes developer article explains the Beta changes to Changed Block Tracking (CBT) support for CSI drivers. The SnapshotMetadataService CRD moved from v1alpha1 to v1beta1, with no automatic conversion, and CBT remains limited to block volumes. It also outlines compatibility requirements and the steps for upgrading and trying the feature. ### Source excerpt Changed Block Tracking (CBT) support for CSI drivers shipped as Alpha in September 2025. With the March 2026 v1.0.0 release of the external-snapshot-metadata project, the feature moved to Beta. If you aren't yet familiar with changed block tracking for storage in Kubernetes, the Alpha announcement covers the motivation, the three primary components (the CSI SnapshotMetadata gRPC service, the SnapshotMetadataService CRD, and the external-snapshot-metadata sidecar), and a walkthrough of how to use the API. CBT currently applies to block volumes; file-volume and network file-share changed-list tracking is not covered by this feature. This post focuses on what is different in Beta. What's new in Beta The main change in that release was the promotion of the SnapshotMetadataService CRD from v1alpha1 to v1beta1. The CRD used to advertise a driver's metadata service now serves cbt.storage.k8s.io/v1beta1. The schema itself is unchanged, but this release removed v1alpha1 (rather than serving it alongside the new version). If you are upgrading from Alpha, you need to: Re-apply the CRD definition shipped with v1.0.0. Update SnapshotMetadataService manifests to use apiVersion: cbt.storage.k8s.io/v1beta1. Update any client or controller code that talks to the CRD. This is a one-time change. There is no automatic conversion between the two versions. Compatibility Minimum Kubernetes version: 1.33 CSI spec: 1.10 or newer Container image: registry.k8s.io/sig-storage/csi-snapshot-metadata:v1.0.0 Trying it out The Getting Started section in the Alpha blog still applies. In short: Make sure your CSI driver supports volume snapshots and ships the external-snapshot-metadata sidecar. Install the SnapshotMetadataService CRD (the v1beta1 definition from the v1.0.0 release). Create a SnapshotMetadataService resource for your driver. Use a client -- snapshot-metadata-lister, or your own implementation -- to call GetMetadataAllocated and GetMetadataDelta. If you want to see the full flow end-to-e ## Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2 DevFeed: [Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-10T20:40:57Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [AI Infrastructure](), [cloud-infrastructure](), [Cloud](), [data-processing](), [model-deployment]() Tags: [accelerators](), [ai](), [ai-infrastructure](), [cloud](), [cloud-storage](), [data](), [datasets](), [enterprise](), [inference](), [infrastructure](), [integration](), [performance](), [snapshots](), [storage]() ### AI overview Backblaze and WEKA validated a two-tier AI storage pipeline that uses WEKA NeuralMesh as the high-performance tier for GPU workloads and Backblaze B2 Cloud Storage as the capacity tier. Raw data, training sets, media, source files, checkpoints, and other assets can move between the tiers according to access needs. NeuralMesh's Snap-to-Object feature was also tested with B2 for storing consistent filesystem snapshots and supporting recovery. ### Source excerpt Backblaze and WEKA have validated their two platforms together for AI pipelines, pairing WEKA NeuralMesh as the performance tier that feeds GPUs with Backblaze B2 Cloud Storage as the capacity tier that holds everything else. The integration, sizing, tuning, and testing are already done, so an AI infrastructure team can deploy a proven two-tier layout The post Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2 appeared first on StorageReview.com. ## I moved my laptop to a rolling-release distro and the snapshots did the heavy lifting DevFeed: [I moved my laptop to a rolling-release distro and the snapshots did the heavy lifting]() Original publisher: [Read original article]() Author: Shed Stack Published: 2026-09-06T18:00:00Z Content type: opinion Language: en Sources: [Shed Stack]() Topics: [btrfs](), [Kernel](), [Hardware]() Tags: [boot](), [bootloader](), [btrfs](), [driver](), [laptop](), [packages](), [rollback](), [snapshots](), [update]() ### AI overview The author describes moving a laptop to CachyOS, a rolling-release distribution, to obtain newer kernels and packages. Automatic Btrfs snapshots managed with snapper provide rollback protection when updates affect boot components, drivers, or the desktop. ### Source excerpt CachyOS, snapper, and the DPTF fix. What a rolling release is actually like when you keep a parachute. ## BTRFS boot failure and easy GUI methods for system recovery DevFeed: [BTRFS boot failure and easy GUI methods for system recovery]() Original publisher: [Read original article]() Author: Alex Genovese Published: 2026-09-04T20:54:40Z Content type: article Language: en Sources: [Fedora Magazine]() Topics: [boot](), [Fedora](), [GUI](), [Linux](), [dnf](), [Software]() Tags: [backup](), [boot](), [btrfs](), [desktop](), [dnf](), [faqs-and-guides](), [fedora-project-community](), [for-system-administrators](), [gui](), [how-to](), [installation](), [iso](), [linux](), [recovery](), [snapshots](), [usb](), [using-hardware](), [using-software](), [workstation]() ### AI overview This how-to article explains GUI-based recovery options for Fedora Linux systems using BTRFS. It covers booting from a USB live ISO, checking whether the operating system uses BTRFS, and recovering earlier system states with snapshot tools such as btrfs-assistant and snapper. ### Source excerpt A few short how-to's with screenshots, showing easy ways to boot up off a USB live ISO and return back to previous points in time with BTRFS ## Announcing DocumentsDB: Documents that evolve with your product DevFeed: [Announcing DocumentsDB: Documents that evolve with your product]() Original publisher: [Read original article]() Author: Arnab Chatterjee Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Databases](), [GeoJSON](), [SDKs]() Tags: [announcements](), [database](), [json](), [product](), [products](), [scheduled](), [sdk](), [snapshots](), [transactions]() ### AI overview Appwrite announces DocumentsDB, a schemaless database for flexible JSON documents whose fields can evolve without defining columns or running schema migrations. It supports Appwrite SDK patterns and database capabilities such as permissions, queries, transactions, bulk operations, imports, exports, and backups. ### Source excerpt Store flexible JSON documents, query them with the Appwrite SDKs, and let your data model evolve with your product instead of ahead of it. ## Vercel Sandbox is now globally available DevFeed: [Vercel Sandbox is now globally available]() Original publisher: [Read original article]() Author: Rob Herley Published: 2026-08-24T04:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Command-line interface](), [SDKs](), [Latency](), [cloud-infrastructure]() Tags: [cli](), [databases](), [documentation](), [enterprise](), [latency](), [object-storage](), [reduce](), [sdk](), [snapshots](), [vercel]() ### AI overview Vercel Sandbox is now globally available in four regions, with region selection supported on all plans and configurable failover regions for Pro and Enterprise teams. ### Source excerpt Vercel Sandbox now runs globally, starting with four regions: iad1 (Washington, D.C.), sfo1 (San Francisco), cle1 (Cleveland), and cdg1 (Paris). iad1 remains the default. Support for all Vercel regions is coming soon. Choose a region close to the databases, object storage, and other services your sandboxes access to reduce latency. Region selection is available on all plans. Pro and Enterprise teams can also configure failover regions. If the primary region is unavailable, new sandboxes start in the closest configured failover region. Failover only applies to regions you configure; without it, a sandbox starts in its selected region, or the project default. Update the SDK or CLI you use to the latest version: Configure the default region and failover regions from Settings > Sandboxes in your project, or with the Vercel CLI: Those defaults apply to every sandbox. To override them for a single sandbox, pass region and optionally failoverRegions at create time with the SDK: Or with the CLI: Learn more in the Sandbox regions documentation. Read more ## Incremental backup on AWS Glacier with rustic DevFeed: [Incremental backup on AWS Glacier with rustic]() Original publisher: [Read original article]() Published: 2026-08-19T21:04:01Z Content type: tutorial Language: en Sources: [Personal blog of Anurag Bhatia]() Topics: [backups](), [restic](), [Amazon Web Services](), [Amazon S3](), [Rust](), [Open Source](), [Feathers]() Tags: [aws](), [aws-glacier-deep-archive](), [backblaze-b2](), [backup](), [backups](), [client](), [config](), [cost](), [data](), [encryption](), [encryption-at-rest](), [incremental](), [lifecycle](), [open-source](), [password](), [restic](), [restore](), [rust](), [rustic](), [s3](), [snapshots]() ### AI overview A practical guide to using rustic, a Rust implementation compatible with restic, for incremental backups with AWS Glacier cold storage. It explains keeping backup data in cold storage while maintaining metadata in S3 Standard or Backblaze B2 so snapshots, incremental backups, and targeted restores remain possible. ### Source excerpt I have been a heavy restic user for several years. In Jan of this year, I tried making restic work with AWS Glacier deep archive but it did not work out. AWS Glacier Deep Archive, for those who may not know, is one of the cheapest storage options, with costs as low as $1/TB, but with very expensive retrieval due to high egress charges from AWS, in addition to retrieval fees, API charges, etc. It can act as a backup of last resort, kind of like insurance if everything else fails, since it costs roughly 1/7th of what Backblaze B2 charges for the same data ($6.95/TB/month). Restic by design is not compatible with Glacier because it stores a mix of data blobs and tree blobs inside /data. Thus, as AWS lifecycle rules move data from S3 Standard to Glacier, basic repo operations start failing. They do have some experimental support as per FAQ, but it did not work out for me when I tried in Jan. A few days back, I came across an open-source project named rustic -- it's a restic implementation in Rust and supports cold storage. The rustic client is compatible with a traditional restic repo. Rustic and cold storage Rustic supports AWS Glacier as well as OVH cold storage. The way it works is: they keep all data in cold storage and a copy of the metadata in hot storage. This additional copy of metadata in hot storage allows operations like incremental backups, viewing snapshots, and requesting restores where only the specific data blobs needed for the restore are pulled from Glacier. This additional hot storage can sit on S3 standard or even Backblaze B2 (which I prefer due to zero API cost). Demo 1) Create repo Let's create two buckets - one in S3 (to store data in Glacier) and one on Backblaze B2 to hold an additional copy of metadata. > rclone mkdir s3:rustic-demo-cold > rclone mkdir b2:rustic-demo-hot 2) Create rustic config profile This file will define the cold and hot repo locations, along with the password file location, restoration command syntax, etc. [repository] repo ## From slow tests to slow production: Debugging with Stackprof DevFeed: [From slow tests to slow production: Debugging with Stackprof]() Original publisher: [Read original article]() Published: 2026-08-13T00:00:00Z Content type: tutorial Language: en Sources: [Aha! Engineering Blog]() Topics: [debugging](), [Tooling](), [RSpec](), [Databases]() Tags: [ci](), [cpu-time](), [database](), [debugging](), [logs](), [overhead](), [performance](), [production-debugging](), [profiling](), [rspec](), [snapshots](), [tests](), [timing]() ### AI overview An investigation into tests that became six times slower traces the stall to code generating example data and Active Record callbacks. The article explains using Stackprof with RSpec to profile the test, including I/O time, and reports that the test spent 71% of its time sleeping. ### Source excerpt One morning, a developer announced in our Slack channel that some tests were failing on our main branch. The cause of the failures was not obvious. No recent PRs seemed related, and neither the code nor the tests had changed in a long time. The test ## Connect to and manage Sandboxes from the dashboard DevFeed: [Connect to and manage Sandboxes from the dashboard]() Original publisher: [Read original article]() Author: Marc Codina Segura Published: 2026-07-23T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [dashboards](), [Vercel](), [browser]() Tags: [browser](), [filesystem](), [sandbox](), [sandboxes](), [snapshots](), [vercel]() ### AI overview Vercel now lets users connect to running Sandboxes from the dashboard to run commands, browse files, transfer files, and inspect open ports. Users can also take snapshots and stop or resume persistent sandboxes from the same interface. ### Source excerpt You can now connect to any running Sandbox from the Vercel dashboard. Run commands, browse the filesystem, upload and download files, and inspect open ports without leaving the browser. From the same view, you can also manage the sandbox lifecycle: take snapshots, and stop or resume persistent sandboxes. Open the Connect tab on any sandbox to try it out. Learn more about Vercel Sandboxes in the documentation. Read more ## New: Versioned CLI and SDK Docs DevFeed: [New: Versioned CLI and SDK Docs]() Original publisher: [Read original article]() Author: Cam Soper Published: 2026-07-07T00:00:00Z Content type: release Language: en Sources: [Pulumi]() Topics: [Documentation](), [SDKs](), [Command-line interface]() Tags: [announcements](), [api](), [cli](), [community](), [docs](), [features](), [github](), [issue](), [java](), [net](), [node-js](), [product](), [pulumi](), [pulumi-cli](), [python](), [release](), [sdk](), [snapshots]() ### AI overview Pulumi has added version selectors to its CLI command reference and SDK API documentation. Users can choose documentation matching the Pulumi release they are running, with immutable snapshots available from v3.150.0 onward for the CLI and Node.js, Python, .NET, and Java SDKs. ### Source excerpt Pinned to an older Pulumi CLI or SDK version and finding that the docs describe a newer release? The Pulumi CLI command reference and the SDK API docs now include a version selector, so the documentation you're reading matches the version you're actually running. How it works When you open the CLI command reference, you'll see a version dropdown near the top of the page, below the title. The SDK API docs carry the same dropdown in the upper-right corner. Choose a release, and the page loads the documentation generated for that exact version. What's available Alongside the latest release, we keep immutable snapshots of previous versions going back to v3.150.0 (early 2025). The CLI command reference and the Node.js, Python, .NET, and Java SDK API docs are all covered, so the docs you need are only a dropdown away. (The Go SDK is versioned on pkg.go.dev, so its documentation lives there rather than in the Pulumi docs.) Get started Head to the CLI command reference or the SDK API docs and try the version dropdown. Selections are sticky, so when you navigate into a version, you'll be able to click around within that same version without having to choose it again. Have feedback? Let us know in the Pulumi Community Slack or by opening an issue on GitHub. Browse the CLI command reference ## Vercel Sandbox now support Custom Images DevFeed: [Vercel Sandbox now support Custom Images]() Original publisher: [Read original article]() Author: Tom Lienard Published: 2026-06-30T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [toolchain](), [Docker](), [boot]() Tags: [boot](), [compute](), [container-registry](), [dependencies](), [docker](), [documentation](), [filesystem](), [images](), [os](), [performance](), [registry](), [sandbox](), [sandboxes](), [snapshots](), [toolchain](), [vercel]() ### AI overview Vercel Sandboxes now support custom images in public beta. Users can provide a custom root filesystem with their own operating system, toolchain, and dependencies. Images are pulled from Vercel Container Registry, and the feature is designed to preserve cold start performance through precompiled snapshots. ### Source excerpt Vercel Sandboxes now supports custom images. Launching in public beta today, images allow Sandboxes to start with your own custom root filesystem. Images are pulled from Vercel Container Registry, so anything you docker push is immediately available. Bring your own OS, toolchain and dependencies into the Sandbox without needing to spin up compute and create Snapshots. Images in the background for Fluid Compute and boot from a precompiled snapshot in the same format as our Sandbox Snapshots - so you get the convenience of a custom filesystem without sacrificing cold start performance. Read more about running images with Sandbox in the documentation. Read more ## Sandboxes now expire based on last use DevFeed: [Sandboxes now expire based on last use]() Original publisher: [Read original article]() Author: Marc Codina Segura Published: 2026-06-29T01:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Persistence]() Tags: [persistence](), [retention](), [sandboxes](), [snapshots](), [time](), [vercel](), [workflows]() ### AI overview Vercel Sandbox snapshots now expire according to their last use rather than their creation time. Using a snapshot resets its expiration timer, allowing active workflows to keep dependent snapshots available while unused snapshots follow their retention policy. ### Source excerpt Vercel Sandbox snapshots now expire based on when they were last used, not when they were created. Active snapshots stay alive as long as workflows depend on them, while unused snapshots expire on their retention policy. Every time a snapshot is used, its expiration timer resets. This lets you set shorter retention windows without worrying that a snapshot will disappear between sessions, making it safer to build long-running workflows on top of Sandbox persistence. Learn more about Sandbox snapshots in the documentation. Read more ## Sandbox persistence is now GA DevFeed: [Sandbox persistence is now GA]() Original publisher: [Read original article]() Author: Harpreet Arora Published: 2026-05-26T00:01:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Persistence](), [Vercel](), [Command-line interface](), [SDKs]() Tags: [cli](), [compute](), [filesystem](), [fork](), [network](), [persistence](), [sandbox](), [sdk](), [snapshots](), [storage](), [upgrade](), [vercel](), [workflow]() ### AI overview Vercel Sandboxes now provide generally available persistence. Filesystem state is automatically saved and restored between sessions, with persistence enabled by default and sandboxes addressable by durable names. Users can opt out for ephemeral workloads, while persistent sandboxes resume from the latest snapshot automatically. ### Source excerpt Vercel Sandboxes now automatically save and restore filesystem state between sessions. Persistence is on by default, meaning no snapshots to manage or state to track manually. Each sandbox has a durable, customizable name that acts as a unique reference in your project. You can create, retrieve, or resume a sandbox by name. Vercel spins sessions up and down automatically, without interrupting your workflow. Create a persistent sandbox When you call Sandbox.create(), persistence is enabled by default: Each automatic snapshot consumes snapshot storage, which is billed separately from compute. For ephemeral workloads, opt out of persistence to minimize storage costs: To opt out of persistence with the CLI, pass --non-persistent to sandbox create. Non-persistent sandboxes discard their filesystem when the session ends. Resume a persistent sandbox Resuming is automatic. Any call on a stopped sandbox, like runCommand() or writeFiles(), starts a new session from the most recent snapshot. Other improvements Sandbox.fork(): Create a new sandbox from an existing one Sandbox.getOrCreate(): Idempotent retrieve-or-create for long-lived sandboxes Sandbox.delete(): Permanently delete a sandbox Richer sandbox.stop(): Returns snapshot metadata plus active-CPU and network-transfer totals Lifecycle hooks: onCreate and onResume hooks for create, get, and getOrCreate Tags: Assign custom properties to sandboxes for multi-tenant tracking Get started Upgrade to the latest version to create persistent sandboxes by default: pnpm install @vercel/sandbox@latest # SDK pnpm install -g sandbox@latest # CLI Learn more about persistent sandboxes in the documentation. Read more ## Writing interactive screenshot tests in Compose UI with Touch Robot DevFeed: [Writing interactive screenshot tests in Compose UI with Touch Robot]() Original publisher: [Read original article]() Author: Saket Narayan Published: 2026-05-24T06:09:55Z Content type: tutorial Language: en Sources: [Saket Narayan]() Topics: [Compose](), [screenshot-testing](), [ui-testing](), [Testing]() Tags: [android](), [compose](), [screenshot-testing](), [snapshots](), [testing](), [ui-testing]() ### AI overview The article explains how Block built Touch Robot to generate fake touch events for interactive screenshot tests in Compose UI. It describes using animated PNG snapshots to verify interactions such as clicks, swipes, drawing, and pinch gestures, with deterministic frame comparisons for regression testing. ### Source excerpt These are some examples of real issues that were happening at Block. Each of them was frustrating because we were regularly shipping broken experiences to customers despite having sufficient test coverage. We had screenshot tests using Paparazzi, but they were mostly static snapshots that verified layout correctness. We had connected device tests, but they ran [...] The post Writing interactive screenshot tests in Compose UI with Touch Robot appeared first on Saket Narayan. ## Practicing Playwright: Visual Testing With Playwright DevFeed: [Practicing Playwright: Visual Testing With Playwright]() Original publisher: [Read original article]() Author: T.J. Maher (noreply@blogger.com) Published: 2026-05-21T12:46:54Z Content type: tutorial Language: en Sources: [T.J. Maher]() Topics: [Playwright](), [Testing](), [Docker](), [ci](), [WebKit](), [Chrome](), [Firefox]() Tags: [chrome](), [ci](), [docker](), [firefox](), [playwright](), [snapshots](), [software-testing](), [testing](), [visual-testing]() ### AI overview This tutorial demonstrates Playwright visual testing by capturing screenshots of pages or elements, comparing them with baseline snapshots, and using masking to exclude changing content. It also discusses browser and operating-system differences, repository size, and running visual tests in a standardized CI environment. ### Source excerpt If you want to do some basic visual checking to see if there has been any deviation from your baseline of images, you can use Playwright. It's built in! Playwright can take a snapshot of a web element, a visible viewport, or a full page, and save it in your Git repository as a baseline, failing the test if the image, page, or viewport does not match up. Caution: From what I have been reading, this can quickly cause your code repository to balloon in size, since Chrome, Firefox, and WebKit would each store its own golden screenshot in your repo. Also, images on Mac, Windows, and Linux all appear different pixel-by-pixel. If using a CI platform, it might be best to run visual tests only on a standard Playwright Docker image, to generate and compare snapshots. According to TestQuality, "Once a suite passes 50-100 visual tests, teams need a layer that tracks run history, surfaces flaky-test patterns across cycles, and routes confirmed defects into the team's tracker -- none of which lives inside the test runner itself"... I wonder if you can store images in an Amazon S3 bucket and hook that up as a virtual drive? ... no matter. That will be a blog post for another time... Right now, we will be walking through Butch Mayhew's code he wrote for his LinkedIn Learning course, Learning Playwright, found on his companion GitHub site. While the test is in a certain state you can a screenshot of the page or certain elements of the page and save them as a snapshot. The snapshots an be used as a baseline images to compare your current site against. This baseline can be periodically updated as the site evolves. How does this happen? With Playwright's .toHaveScreenshot( ) to take a screenshot and the mask method that you want to leave out of the comparisons between the expected and actual screenshots. toHaveScreenshot(name): Playwright.dev / Page Assertions Our Test Site: PracticeSoftwareTesting.com Butch has a series of tests for the test site Practice Software Testing ( practicesof ## AI threats in the wild: The current state of prompt injections on the web DevFeed: [AI threats in the wild: The current state of prompt injections on the web]() Original publisher: [Read original article]() Author: Kimberly Samra (noreply@blogger.com) Published: 2026-04-23T21:38:00Z Content type: article Language: en Sources: [Google Online Security]() Topics: [prompt injection](), [Artificial Intelligence](), [Security](), [Threat Research](), [Vulnerabilities](), [Google](), [AI Chat]() Tags: [ai](), [ai-agents](), [google](), [none](), [prompt](), [prompt-injection](), [research](), [security](), [snapshots](), [threat-intelligence](), [vulnerabilities]() ### AI overview Google Threat Intelligence teams describe a public-web investigation into indirect prompt injection, an attack in which malicious instructions embedded in websites, emails, or documents can redirect an AI system away from the user's intent. The article examines whether real-world attackers are operationalizing these attacks and uses Common Crawl snapshots to study known patterns. ### Source excerpt Posted by Thomas Brunner, Yu-Han Liu, Moni Pande At Google, our Threat Intelligence teams are dedicated to staying ahead of real-world adversarial activity, proactively monitoring emerging threats before they can impact users. Right now, Indirect Prompt Injection (IPI) is a top priority for the security community, anticipating it as a primary attack vector for adversaries to target and compromise AI agents. But while the danger of IPI is widely discussed, are threat actors actually exploiting this vector today - and if so, how? To answer these questions and to uncover real-world abuse, we initiated a broad sweep of the public web to monitor for known indirect prompt injection patterns. This is what we found. The threat of indirect prompt injection Unlike a direct injection where a user "jailbreaks" a chatbot, IPI occurs when an AI system processes content--like a website, email, or document--that contains malicious instructions. When the AI reads this poisoned content, it may silently follow the attacker's commands instead of the user's original intent. This is not a new area of concern for us and Google has been working tirelessly to combat these threats. Our efforts involve cross-functional collaboration between researchers at Google DeepMind (GDM) and defenders like the Google Threat Intelligence Group (GTIG). We have previously detailed our work in this area and researchers have further highlighted the evolving nature of these vulnerabilities. Despite this collective focus, a fundamental question remains: to what degree are real-world malicious actors currently operationalizing these attacks? Proactive monitoring at GoogleThe landscape of IPI on the web There are many channels through which attackers might try to send prompt injections. However, one location is particularly easy to observe - the public web. Here, threat actors may simply seed prompt injections on websites in hope of corrupting AI systems that browse them. Public research confirms these attacks are ## Automatic persistence now in beta on Vercel Sandbox DevFeed: [Automatic persistence now in beta on Vercel Sandbox]() Original publisher: [Read original article]() Author: Harpreet Arora Published: 2026-03-26T07:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Persistence](), [Vercel](), [Orchestration](), [SDKs](), [Command-line interface](), [configuration]() Tags: [cli](), [configuration](), [persistence](), [sandbox](), [sandboxes](), [sdk](), [snapshots](), [storage](), [vercel]() ### AI overview Vercel Sandboxes now support automatic filesystem persistence in beta. Stopped sandboxes save their filesystem state and restore it when resumed, while sessions provide the compute associated with that state. The beta SDK enables persistence by default, and the beta SDK and CLI add lifecycle management, configuration, and session inspection capabilities. ### Source excerpt Vercel Sandboxes can now automatically save their filesystem state when stopped and restore it when resumed. This removes the need for manual snapshots, making it easier to run long-running, durable sandboxes that continue where you left off. How it works A sandbox is the durable identity, now identified by a name, its filesystem state, and configuration options. A session is the compute tied to that state, invoked as needed. Automatic persistence introduces orchestration that separates storage from compute, reducing the need for manual snapshotting, so: when you stop a sandbox, the session shuts down but the filesystem is automatically snapshotted. when you resume, a new session boots from that snapshot. This state storage is not charged, so you pay when your setting is active. Persistence is enabled by default in the beta SDK, can be disabled between sessions with persistent: false. When disabled, the sandbox still exists after being stopped and can be resumed by its name, but each session starts with a clean filesystem. If a sandbox is stopped and you run a command, the SDK will transparently create a new session, so you don't need to check state or manually restart The beta SDK adds methods for managing sandboxes over their lifetime: The beta CLI adds configuration management and session inspection: This feature is in beta and requires upgrading to the beta SDK and CLI packages. Install the beta packages to try persistent sandboxes today: pnpm install @vercel/sandbox@beta for the SDK, and pnpm install -g sandbox@beta for the CLI. Persistent sandboxes are available in beta on all plans. Learn more in the documentation. Read more ## Vagrant: entornos de desarrollo reproducibles DevFeed: [Vagrant: entornos de desarrollo reproducibles]() Original publisher: [Read original article]() Author: Antonio Pérez Published: 2026-02-06T00:00:00Z Content type: tutorial Language: es Sources: [tengoping.com]() Topics: [Vagrant](), [Oracle-VM-VirtualBox](), [Linux]() Tags: [ansible](), [hashicorp](), [rsync](), [ruby](), [snapshots](), [vagrant](), [virtualbox]() ### AI overview A Spanish tutorial explaining how Vagrant defines reproducible development environments as code. It covers installation, provider selection, Vagrantfile configuration, the VM lifecycle, SSH access, and synchronized folders, including performance and consistency considerations for VirtualBox, libvirt, NFS, and rsync. ### Source excerpt Vagrant con libvirt o VirtualBox: carpetas sincronizadas, snapshots, aprovisionamiento con Ansible y reload vs provision. ## Three Ways to Use Your Snapshots DevFeed: [Three Ways to Use Your Snapshots]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-11-11T00:54:40Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Database](), [data]() Tags: [architecture](), [backup](), [migration](), [product](), [recovery](), [retention](), [snapshots](), [storage]() ### AI overview Neon's article explains how to use database snapshots, including automatic daily, weekly, and monthly scheduling, point-in-time preservation, instant restoration, production migration safety, and archival beyond a branch's retention period. ### Source excerpt Neon's snapshots feature is now available to all users (in Beta), and you can finally schedule them automatically. You can make snapshots daily, weekly, or monthly from the Backup & Restore page in the Neon Console. Snapshots are built on Neon's copy-on-write architecture: they c... ## Major compute price reduction on Neon DevFeed: [Major compute price reduction on Neon]() Original publisher: [Read original article]() Author: Nikita Shamgunov Published: 2025-11-03T19:23:07Z Content type: release Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [autoscaling](), [databricks](), [cloud-infrastructure](), [Supabase]() Tags: [autoscaling](), [company](), [compute](), [cost](), [cost-savings](), [databases](), [databricks](), [durability](), [infrastructure](), [load](), [serverless](), [snapshots]() ### AI overview Neon announces compute price reductions of up to 25% across its plans, including lower rates for the Launch and Scale Plans. The article also reviews earlier reductions to storage, minimum spend, enterprise features, and Free Plan compute, then compares costs with Aurora Serverless v2 and Supabase in selected usage scenarios. ### Source excerpt Databases are often one of the biggest infrastructure expenses for any company. From day one, Neon's mission has been to make databases radically more efficient through separation of storage and compute, allowing instant autoscaling and better unit economics. Now, with Neon runni... ## Build Checkpoints For Your Agent Using Neon Snapshots DevFeed: [Build Checkpoints For Your Agent Using Neon Snapshots]() Original publisher: [Read original article]() Author: Andre Landgraf Published: 2025-09-16T22:52:22Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [API](), [Database](), [data](), [Serverless](), [Vibe coding](), [Database Migration]() Tags: [agent](), [agentic](), [agents](), [api](), [app](), [architecture](), [backups](), [code](), [coding](), [compare](), [database](), [disaster-recovery](), [feature](), [product](), [rollback](), [serverless](), [snapshots](), [storage](), [vibe-coding]() ### AI overview The article explains how Neon snapshots can provide checkpoints for agent-built applications. Because each checkpoint preserves the application code together with the corresponding database schema and data, users can compare versions and roll back to a consistent state. Neon's API, serverless Postgres architecture, and copy-on-write storage make this approach practical and cost-effective. ### Source excerpt You can now create Neon snapshots via API. This new capability isn't just useful for backups or disaster recovery, but also serves as a powerful building block for one of the most requested features in agentic platforms: versioning (or checkpoints). Neon's snapshots, built on our... ## Why traconiq Migrated Their Multi-TB Telemetry Dataset to Neon DevFeed: [Why traconiq Migrated Their Multi-TB Telemetry Dataset to Neon]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-07-01T16:21:46Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [dataset](), [telemetry](), [Amazon RDS](), [autoscaling](), [Scalability](), [Databases](), [Amazon S3]() Tags: [amazon-rds](), [autoscaling](), [backup](), [case-studies](), [cost](), [dataset](), [postgres](), [real-time](), [s3](), [scalability](), [snapshots](), [storage](), [telemetry]() ### AI overview This article explains why traconiq migrated its multi-terabyte telemetry dataset from Amazon RDS to Neon. It describes rising costs from multiple regions and environments, fixed peak-capacity provisioning despite cyclical load, storage volumes that could not shrink after data was moved to Amazon S3, and the limitations and expense of snapshots for backups. Neon is presented as enabling more efficient scaling through branching and autoscaling. ### Source excerpt "Our workload ingests hundreds of data points per second and our RDS costs were increasing, especially since we had multiple regions and environments. With Neon, we found a way to scale our setup more efficiently, using branching instead of duplicating instances and autoscaling t... ## New Maven Central signing key and snapshot location DevFeed: [New Maven Central signing key and snapshot location]() Original publisher: [Read original article]() Author: Jake Wharton Published: 2025-06-13T00:00:00Z Content type: release Language: en Sources: [Cash App Code Blog]() Topics: [Maven Central](), [Maven](), [Publishing](), [Open Source]() Tags: [end-of-life](), [maven-central](), [open-source-artifacts](), [public-key](), [release](), [server-android](), [signing](), [snapshot](), [snapshots](), [verification]() ### AI overview Cash App migrated its open source artifact publishing to Sonatype's new platform after OSSRH reached end of life. The change introduces a company-wide GPG signing key and moves snapshot builds to the Central Portal Snapshot repository. ### Source excerpt In response to Sonatype announcing the end-of-life for OSSRH, we have migrated to their new publishing platform for our open source artifacts. This is otherwise a transparent change for those who consume these artifacts from Maven Central, but there are two related changes which might affect your builds. [Next page]()