What shipped at Anyshift
A new VictoriaMetrics integration for Annie, a self-verification step that double-checks her findings, and one-click pull request fixes inside reports.
Deep dives into Site Reliability Engineering, AI in production, and scaling infrastructure gracefully. Written by the team building the future of SRE.
Harness runs the production release pipeline and manual approval gate for the checkout-api deployment. Anyshift adds the production impact: affected services, owners, recent changes, and the review decision before the approval waits for a human.
A new VictoriaMetrics integration for Annie, a self-verification step that double-checks her findings, and one-click pull request fixes inside reports.
ServiceNow manages incidents, changes, approvals, and tasks. Anyshift adds production context so those workflows can include cause, blast radius, and owner review.
Postman runs API collections with environments. Anyshift adds the live production context that tells those workflows which API paths, consumers, owners, and monitors actually matter before a release gate runs.
Snyk Container identifies vulnerable image digests. Anyshift joins each digest to Kubernetes runtime, exposure, rollout history, owner, and remediation window.
Annie's root cause analyses now cite only verifiable evidence: logs, traces, metrics, and live infrastructure state, never knowledge-base articles or memory.
Sever the link between a service and its database in our new Playground, and a change event lands. Seconds later the root cause comes back, traced against the topology graph instead of a wall of logs. A hands-on way to see what change-first root-cause analysis does, no signup.
CrowdStrike Falcon helps security teams decide what to do with suspicious domains, IPs, and files. Anyshift shows which services, owners, dependencies, and recent deploys are behind the signal before analysts detect, block, or escalate it.
Confluent validates and registers Kafka schema changes. Anyshift adds the production impact: affected services, owners, monitors, and skipped non-production paths.
Annie (our AI SRE agent) had institutional memory from ACE, the agentic context-engineering loop that curates cheatsheets from past runs. It worked, but clients kept catching her trusting stale entries or missing answers buried in her own bloated context. So we added five things on top: (1) a fixed set of memory items always presented to the agent, (2) per-query retrieval over the rest of the memory store, (3) an agent-optimized index of that store, (4) the ability for the agent to query the store mid-run, and (5) tried-and-true memory freshness mechanisms. Production context, now optimized by the AI using it. Here's the reasoning and what a few weeks in production say.
Coralogix is where SREs investigate telemetry. Anyshift adds the production graph around a signal: affected service, owner, recent deploy, dependency evidence, and skip reasons, then writes the reviewed handoff into a Coralogix Custom Dashboard.
An AI agent in the incident channel can run kubectl and read a dashboard. What it can't do is judge whether the last deploy is the suspect or a red herring. We open-sourced the SRE skills that encode that judgment, runnable offline against fixtures with no credentials.
MongoDB Atlas can alert when a cluster nears its connection limit. Anyshift adds the pre-enable review: affected services, owners, monitors, recent changes, and non-production exclusions before paging starts.
Snowflake is where teams govern data, workloads, and AI workflows. Anyshift adds the live production graph those workflows need before they apply a fix, rerun a task, refresh a dynamic table, or trigger an agentic workflow.
Databricks gives teams the governed data and AI surface. Anyshift adds the live production context a Databricks workflow needs before it patches a data pipeline, reruns a backfill, or calls an agent tool.
GitLab shows reviewers the diff, pipelines, and approvals. Anyshift adds the missing production layer: which live services use the changed code, who owns them, what can be skipped, and who should review before merge.
Okta is where teams manage identity, access, and policy. Anyshift adds production reachability enrichment around an access change: which services, cloud roles, Kubernetes workloads, monitors, and owners sit behind the group before Okta performs the assignment.
Annie now opens pull requests across multiple repos in one request, instead of stopping at the first repository she inspects.
Elastic gives teams the place to search, triage, and open Cases (Kibana investigation tickets) when an incident starts. For a PR that changes a shared authentication module, Anyshift adds what Elastic cannot infer from the PR alone: which production services depend on it, who owns them, Identity hints, and evidence. So when a human or agent starts debugging, the context is already attached.

BeReal's synchronized posting ritual creates sharp traffic waves, not a smooth feed. With Anyshift, the team can route Go panics from unfamiliar services to the right owner in about 30 seconds because Anyshift reads each crash against a maintained infrastructure graph.
Private equity firms are pushing AI across portfolios, but the hard part is no longer experimentation. It is turning sponsor-level AI pressure into governed, production-aware operating workflows that actually move EBITDA.
Planned maintenance often creates alert noise. Anyshift finds the Splunk alerts affected by a change, pauses only those saved searches, and turns them back on when the window ends. Teams keep real alerts visible while expected noise stays out of the way.
Annie can now open a real GitHub pull request from chat with the new Fix - Open PR button, plus a reworked memory layer for larger investigations.
A deployment event should carry the service, owner, and monitored entity it actually changed. Anyshift adds that production context to Dynatrace so on-call teams do not rebuild it from CI and infrastructure tabs.
Teams investigate incidents in New Relic, but deploy context often lands only on the service that changed. Anyshift maps the real production impact, so every affected New Relic entity gets the deployment context.
Sentry is where teams debug regressions. Anyshift makes sure the release context reaches every affected project, including downstream services that did not deploy.
A shared-code PR should not surprise downstream teams after merge. Anyshift finds the running services and owners affected by the change, then routes the advisory work into Jira before the review is over.
Annie gets report personas, per-conversation effort levels, OpsGenie alerts, Sentry/Notion link auto-resolve, and a clearer left sidebar around Root Cause Analysis, Proactive, and Custom Reports.
Datadog pup can mute monitors during maintenance, but teams still have to know which downstream services will be noisy. Anyshift CLI maps the affected services from production context, then prepares the Datadog downtime runbook with an audit trail.
Grafana shows the service you instrumented, but downstream services often miss the same dashboards and SLOs. Anyshift maps the dependency graph, finds the coverage gaps, and prepares the Grafana resources for gcx to apply after review.
Linear and Notion join Annie's knowledge sources, annie-cli gains access-token authentication for headless CI use, and Annie won't recommend silencing alerts.
A development RDS instance had its publicly_accessible flag flipped on a Friday afternoon. The team's drift-detection cadence was once per weekday, so 60+ hours passed before anyone caught it. Walkthrough of the audit-log subscription architecture that would have caught it in two minutes across AWS, GCP, and Azure, with every config block paste-able into your own account.
Burned 25 minutes on a Friday-morning page before I realized the responsible commit was in another team's repo. This is the four-command sequence I now run when an alert lands and `git log` on my own service comes up empty, with the outputs at each step and where the search space gets cut.
Forty minutes paging Linear to confirm a returning customer report was the same bug we'd half-shipped a fix for in February. The Linear integration went GA May 13, and Annie pulled both tickets, the linked PR, and the stalled action in twenty-three seconds.
Ten minutes to find a post-mortem already sitting in Notion. The Notion integration shipped May 12, and Annie picked the same page in eighteen seconds, root cause and open action items tagged.
Datadog gains 50+ Bits AI capabilities; PagerDuty + Incident.io + Sentry join as sources; k8s-agent v0.3.2 brings on-demand graph reconciliation.
Five Sentry tickets in one worker turned out to be one bug. The most-recent error came from the very PR that had wired Sentry forwarding in. How a stack frame now leads to the offending commit, the deploy behind it, and the team that owns the failing path.

Yubo's small SRE team supports 85M users across 140 countries on GCP and GKE, producing 20 TB of logs per day. With Annie running parallel investigations in Slack, peak-hour incidents now resolve in two messages.

Anyshift is now on AWS Marketplace. Buy through your AWS account, bill against your AWS spend, and skip the standalone InfoSec review.
6 product areas shipped: Slack reports, MCP and CLI tools to drive Annie from your terminal, smarter automation rules, tighter AWS onboarding.

How AI agents learn your infrastructure. A walkthrough of the DevOpsCon Amsterdam 2026 talk: the gap between LLMs and production, structural context as a versioned graph, and ACE for self-improvement without labels.

Every Monday, the pod-stability review gets rebuilt from scratch. Same dashboards, same correlation work, same write-up. Two hours, gone. Report Templates turn the recurring investigations platform and SRE teams run by hand into one click.

Temporal workflows stuck in Running with zero pollers, and Temporal still reports a healthy task queue. The root cause lives one layer down: a CrashLoopBackOff in the Kubernetes worker pod, caused by a single bad environment variable. A walkthrough of debugging Temporal workers on Kubernetes the manual way (10 minutes), then with an infrastructure context layer that bridges the two systems (seconds).

136 CloudWatch alarms vanish overnight. Annie cross-references Slack, the audit trail, and your infra graph in one query. Now it runs in your terminal.

The 10 best AI SRE tools in 2026 compared by architecture, root cause analysis, remediation, and change awareness — from Anyshift's versioned graph to Resolve AI's autonomous agents.

AI agents start every run from scratch. ACE (Agentic Context Engineering) gives them institutional memory that evolves through use, cutting root cause analysis time by 30%.

How Anyshift chose Neo4j for building a temporal infrastructure knowledge graph and lessons learned over a year of production use.

The limits of telemetry-only AI approaches to SRE and why topology is the missing piece.

Watch the Anyshift product demo featuring a testimonial from Voodoo.

An interview about the AI that repairs infrastructure breakdowns in 5 minutes.
An interview with Roxane Fischer on how Silicon Valley builds AI products.

Watch the Anyshift product demo featuring a testimonial from Citrix.

Master AWS monitoring with CloudWatch, CloudTrail, AWS Config, and X-Ray for comprehensive observability.

A comprehensive guide to AWS database services including RDS, Aurora, DynamoDB, and ElastiCache.

Deep dive into AWS Lambda covering function configuration, IAM, VPC integration, and monitoring best practices.

Everything you need to know about Amazon S3 configuration, access control, encryption, and lifecycle management.

A guide to AWS Secrets Manager covering secret storage, rotation, access policies, and integration patterns.

Learn about AWS Network Firewall architecture, rule groups, policies, and logging configurations.

A video tutorial by Ned Bellavance explaining Terraform versioning best practices.

Master AWS VPC networking fundamentals including subnets, route tables, gateways, and peering configurations.

Key takeaways from the Civo Navigate SF conference.

Explore Route 53 and DNS management in AWS, including hosted zones, record types, routing policies, and health checks.

A comprehensive guide to AWS IAM covering users, groups, roles, policies, and best practices for secure access management.

A talk recording from DevOpsDays Dallas about the challenges of debugging infrastructure quickly.
![[Featured in Tessl] DevOps with AI: Identifying the impact zone, with Roxane Fischer](/images/blog/devops-with-ai-impact-zone.png?dpl=dpl_EsBrdbR4DuHfaEhqcGcTmzta6ZGi)
A featured interview on Tessl about DevOps with AI and identifying the impact zone.

GenAI is everywhere. But very often, the cool and exciting demos don't work the same way in production.

Managing infrastructure at scale is a complex endeavor that demands meticulous planning, robust tooling, and continuous adaptation.

Anyshift's presentation at the Awesome AI Dev Tools event in September 2024.

Most infrastructure debugging sessions blow past the one-hour mark for the same five structural reasons: scattered visibility across cloud accounts, missing historical state, terraform plan output that hides downstream impact, runbooks that lag the live infrastructure, and post-merger environments that no one has fully mapped. A walkthrough of each, with concrete examples and what reduces the time.

Three structural patterns recur in growing infrastructure orgs: single-repo bottlenecks where dozens of teams share one approval queue, ClickOps and dead IaC code that drift outside any state file, and module version fragmentation that quietly bypasses security patches. A walkthrough of each, with the practices that contain the blast radius.
Exploring the intersection of AI and DevOps, covering best practices, insights, and practical applications for modern infrastructure teams.
EngineeringTechnical deep dives into Anyshift's engineering decisions, architecture, and lessons learned.
ProductThe latest product updates, feature launches, testimonials, and news from Anyshift.
ExpertA comprehensive series exploring AWS resources in depth, covering best practices and Terraform configurations for each service.
AdvancedAdvanced tutorials and guides on maintaining reliable cloud infrastructure.

Anyshift shares the latest product updates, feature launches, and news from the team.

Ghazi Felhi is an AI Engineer at Anyshift with a PhD in Generative AI, specializing in Language Modeling. A published AI researcher, he brings a track record of productionizing innovative AI-based solutions to Anyshift, where he works on Annie, Anyshift's AI SRE.

Louis Fradin is a DevRel and Backend Engineer at Anyshift, where he's helping build the AI context layer for production systems, giving teams the infrastructure graph they need so AI agents can actually understand what's running in prod.
His path to SRE started deep in the stack: four years writing Linux drivers and managing HPC infrastructure for the French Ministry of Armed Forces, followed by three and a half years at Ubisoft building and operating Kubernetes clusters at scale for game servers with Go, Temporal, Talos, or OpenTelemetry.
Today he bridges that engineering background with developer advocacy, advocating for better observability primitives and smarter AI tooling for the people keeping systems alive.

Mattias is a cloud architect consultant working to help customers improve their cloud environments. He has extensive experience with both the AWS and Microsoft Azure platforms and holds professional-level certifications in both. He is also a HashiCorp Ambassador and an author of a book covering the Terraform Authoring and Operations Professional certification.

Ned is an IT professional and educator with more than 20 years of experience in the field. He has been a helpdesk operator, systems administrator, cloud architect, and product manager. In 2019, Ned founded Ned in the Cloud LLC to work as an independent educator, creator, and consultant. Ned is a Microsoft MVP since 2017 and a HashiCorp Ambassador since 2020.

With a passion for innovation and a deep understanding of cloud infrastructure, Roxane Fischer leads Anyshift.io with a vision to transform how companies manage and maintain their cloud environments. Her background as an ex-Lead Engineer and AI researcher gives her a unique ability to anticipate industry needs, driving Anyshift's growth by delivering solutions that prioritize efficiency, reliability, and long-term success.

With over 20 years of experience in the infrastructure space, Stephane Jourdan is a true authority on building scalable, resilient systems. As the author of the Infrastructure-as-Code Cookbook and former Co-Founder & CTO at CloudSkiff (creators of driftctl, acquired by Snyk), his depth of knowledge in cloud architecture and automation is unmatched.
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