What is Anyshift and how does it work?

Anyshift is an AI SRE platform. It continuously maps your entire infrastructure (cloud providers, Kubernetes, codebases, monitoring tools) into a versioned resource graph, then uses AI to identify root causes during incidents, detect risks proactively, and accelerate onboarding for new engineers.

How does Anyshift detect root causes during incidents?

Anyshift's AI agent, Annie, uses a continuously-updated, versioned resource graph that maps all dependencies across your infrastructure. When an incident occurs, Annie traces the cascade of failures through the graph to pinpoint the original root cause, reducing MTTR from hours to minutes.

What infrastructure providers does Anyshift integrate with?

Anyshift integrates with major cloud providers (AWS, GCP, Azure), container orchestration (Kubernetes), infrastructure-as-code tools (Terraform), monitoring platforms (Datadog, PagerDuty), version control systems (GitHub, GitLab), and more. The versioned resource graph syncs continuously across all connected systems.

Is Anyshift SOC 2 compliant?

Yes, Anyshift is SOC 2 Type II certified and GDPR compliant. The platform is built with enterprise-grade security, and all infrastructure and processes are continuously audited.

Your prod-as-a-graphversioned

Integrations

20+ Integrations

Tap directly$ annie askMCPNo console-hopping

Connect integrations to map your infrastructure

The Platform

The foundation:
Your Prod as a Graph.

A versioned infrastructure graph is a continuously-synced map of your entire production environment: cloud, Kubernetes, codebases, and monitoring. Every state change is tracked with full history, so you can ask “what changed?”

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What’s in the graph

Cloud, K8s, code, monitoring, ops, all on one continuously-synced topology.

Every resource, every change, every signal across your stack — connected, versioned, and remembered.

Cloud & K8s

Resources, services, dependencies

Cloud accounts and Kubernetes clusters, mapped down to the EC2 instance, RDS, deployment, and HPA, with dependencies between them.

Code & config

Linked back to the commit

Repositories, deployments, and config changes link to the resources they shape. Every deploy ties to a commit, every drift to a diff.

Observability & ops

Alerts wired to services

Datadog monitors, PagerDuty routes, Jira tickets, Slack channels, and post-mortems on the same graph. An alert points at the service, the deploy, and the ticket that owns it.

Versioned

Every state change, kept

Not a snapshot. Every state change is timestamped, so Annie can diff “what was true 4 hours ago” against now and pin the change that broke it.

Blast radius

Walk from any change to what it touched.

Every state change is on the graph, wired to the resources it shaped. Annie hops forward from a config edit to the services it broke and the alerts it raised, and backward from an alert to the change behind it.

T − 6hDeploy api-service @ 7af3a91
T − 3hHPA threshold lowered to 65%
T − 1hRDS provisioned IOPS reduced
T − 15mFirst 500s appear
NowAnnie pinpoints the HPA edit

What Annie does on top of it

Investigation, knowledge, and prevention.

Automated Root Cause

Root cause in seconds, not hours. Annie traverses your versioned resource graph to pinpoint exactly what broke and why.

Knowledge Base

Ask Annie “what changed?” She queries a versioned graph of your entire stack and delivers senior-SRE-level insight, with sources, in seconds.

Proactive Annie

Stop firefighting, start preventing. Annie scans your versioned resource graph for missing monitors, node pool upgrades or degradation. And warns you before it matters.

Root Cause Analysis

From alert to root cause in seconds.

When an incident fires, Annie traverses the versioned resource graph across code deploys, infrastructure changes, and monitoring signals to isolate the exact failure point. No more log diving: just the answer.

Alert correlation across deploys, configs, and infrastructure

When an incident fires, Annie correlates the alert against recent code deploys, config changes, and infrastructure faults automatically. No manual triage step.

Cascade tracing through the versioned graph

Annie follows the dependency chain from symptom to source, walking the versioned resource graph across services to surface the cascade root rather than the loudest alert.

Commit-level pinpointing

The result is the exact commit, config diff, or resource change that caused the incident, not a list of suspects. Mean-time-to-root-cause drops from hours to seconds.

Intelligent Infrastructure Assistant

One question replaces ten console tabs.

Annie is a queryable assistant over your entire production environment. Ask plain-English questions about deployments, commits, dependencies, config changes, and monitoring data, all backed by a versioned graph that remembers every state change. She draws on historical incidents, Jira tickets, Slack threads, and post-mortems, and can generate Mermaid diagrams to visualize dependencies and blast radius.

Live state queries across cloud, Kubernetes, code, and monitoring

Annie queries live infrastructure state directly: cloud accounts, Kubernetes clusters, deployments, source repos, and monitoring backends, without console-hopping or stitched-together CLI sessions.

Plain-English Q&A with full context

Ask in natural language. Answers come back enriched with historical incidents, runbooks, and post-mortems, and adapt to your team’s architecture patterns and custom terminology.

CLI, MCP, web, and Slack surfaces

Available where engineers already work: as a CLI, an MCP server, a web dashboard, and a Slack app. No tab-switching to ask a question.

Continuous Protection

Fix it Tuesday, not 3 AM Saturday.

Annie continuously scans your versioned resource graph for missing monitors, node pool upgrades, and early signs of degradation, flagging risks while there is still time to act.

Missing monitors and observability gaps

Annie continuously scans your versioned resource graph for services without alerts, dashboards without owners, and observability gaps that hide degradation until it becomes an incident.

Pending upgrades, EOL versions, and misconfigurations

Node pool upgrades, EOL Kubernetes versions, drifted Terraform state, and resource misconfigurations get flagged with enough lead time to fix on a Tuesday rather than a Saturday.

Actionable recommendations, not just alerts

Each finding ships with a specific recommendation: the manifest to update, the IAM policy to tighten, the alert to add. Not a generic “you have a problem.”

Where Anyshift fits

AI SRE, root cause, agentic AIOps, incident response: one graph behind all of it.

Anyshift as an AI SRE platform

An AI SRE platform automates the reliability work that on-call engineers historically do by hand: incident triage, root cause analysis, runbook execution, and risk prevention. Anyshift fits this category by giving its agent, Annie, a versioned resource graph that spans cloud accounts, Kubernetes clusters, codebases, and monitoring backends. Annie investigates incidents, answers infrastructure questions, and flags missing monitors or pending upgrades before they page anyone, all grounded in the graph rather than guessed from logs.

Anyshift as an AI root cause analysis platform

An AI root cause analysis platform reduces mean-time-to-root-cause by correlating an incident against every recent change across the stack and surfacing the originating fault. Anyshift does this by walking a versioned graph of cloud resources, Kubernetes state, code deploys, and config changes. Every state change is timestamped, so Annie can diff what was true four hours ago against now and pinpoint the exact commit, manifest, or IAM edit behind the cascade. The output is one change, not a list of suspects.

Anyshift in the agentic AIOps category

Agentic AIOps platforms use autonomous AI agents to detect, investigate, and act on operational signals instead of routing every alert to a human. Anyshift’s Annie is one such agent: she queries the live infrastructure graph through MCP, CLI, web, and Slack surfaces, traces dependencies across cloud and Kubernetes, and generates Mermaid blast-radius diagrams on demand. Unlike alert-routing AIOps tooling, Annie’s investigations are grounded in versioned graph state, not statistical pattern matching on log streams.

Anyshift as an AI-powered incident response tool

AI-powered incident response tools cut the time between page and resolution by automating the highest-toil parts of the on-call workflow: triage, correlation, and root cause. During an incident, Anyshift correlates the alert against recent deploys, config changes, and infrastructure faults, walks the dependency chain through the versioned resource graph, and surfaces the originating change without manual log diving or console-hopping. Annie ships in Slack, as a CLI, and as an MCP server, so the answer arrives where the on-call already lives.