Ecosystem
All articles filed under Ecosystem.
10 Articles
Anyshift meets Databricks: production-aware agents on the lakehouse
Databricks is where teams build governed data and AI agents. Anyshift adds the live production graph those agents need before they remediate: services, owners, cloud and Kubernetes dependencies, monitors, recent changes, and blast radius.
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 Splunk: reduce maintenance alert fatigue
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.
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: change impact on every affected entity
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.
Anyshift meets Sentry: releases that follow impact
Sentry is where teams debug regressions. Anyshift makes sure the release context reaches every affected project, including downstream services that did not deploy.
Annie do + acli: route PR impact to Jira
Jira tracks the ticket for an engineering PR, but the PR often hides which production services and teams it will affect. Anyshift maps the impacted services and owners before merge, so the right Jira advisories land on the right team boards.
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.