Stephane Jourdan
CTO & Co-Founder
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.
25 Articles
From Hotspot to Guardrail With Annie Graph
Use Annie Graph to inspect production hotspots, review posture evidence, and enforce explainable reliability or security checks in CI.
Reconstruct a Restart Storm With Annie Graph
Use Annie Graph to move from a production hotspot to an evidence-backed incident timeline, triage result, and operational handoff without an LLM.
Map Production Blast Radius With Annie Graph
Use Annie Graph to trace shared dependencies, calculate transitive production impact, and generate Mermaid topology before making a change.
Annie Graph: 19 Production Queries From Your Terminal
Annie Graph gives platform teams 19 deterministic, read-only commands for production discovery, change planning, incident response, and automation.
Anyshift meets Harness: production-aware approvals
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.
Anyshift meets Dash0: write production-change context into service timelines
Dash0 shows the telemetry. Anyshift writes the upstream production-change context into Dash0 as OpenTelemetry service events for every affected service.
Anyshift meets Redis: Production context before AI agents act
Anyshift adds live production context to AI agents using Redis, then writes the enriched context back to Redis before an AI agent acts.
Anyshift meets ServiceNow: production context for incident workflows
ServiceNow manages incidents, changes, approvals, and tasks. Anyshift adds production context so those workflows can include cause, blast radius, and owner review.
Anyshift meets Postman: production-impact API checks before release gates run
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.
Anyshift meets CrowdStrike: safer threat response with production context
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.
Approve Confluent schema changes with production impact
Confluent validates and registers Kafka schema changes. Anyshift adds the production impact: affected services, owners, monitors, and skipped non-production paths.
Anyshift meets Coralogix: turning telemetry into reviewed production handoffs
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.
Anyshift meets MongoDB Atlas: production-aware alert settings
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.
Anyshift meets Snowflake: production context before agents act
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.
Anyshift meets Databricks: checking production impact before a data pipeline rerun
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.
Anyshift meets GitLab: production impact before merge
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.
Anyshift meets Okta: production reachability for access changes
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.
Anyshift meets Elastic: debug with PR context already attached
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.
Anyshift meets Dynatrace: graph context for every deploy
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.
Anyshift meets New Relic: track shared changes across services
Anyshift finds the production services affected by a shared change, then prepares a reviewed New Relic Change Tracking event for each service's timeline.
Anyshift meets acli: PR impact, routed into Jira
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.
Anyshift meets pup: turning intent into audited Datadog runbooks
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.
Anyshift meets gcx: cloning Grafana observability with audited runbooks
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.
Annie CLI
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.
Building a Temporal Infrastructure Knowledge Graph: A Year of Working with Neo4j at Scale
How Anyshift chose Neo4j for building a temporal infrastructure knowledge graph and lessons learned over a year of production use.