Know Your Blast Radius Before You Deploy.
Blast Radius analyzes your live Elasticsearch data to score every at-risk service before code ships — so your on-call team isn't the first to know something broke.
Every Deploy Is a Guess at What You Don't Know.
Undocumented Dependencies
Your dependency docs are six months behind your actual architecture. Services that were never supposed to talk are talking. And no one has the full picture anymore — not your SRE team, not your architects, not your on-call runbooks.
The Fire Drill Tax
A routine deployment hits an undocumented service. Escalations start. Three engineers are pulled from feature work. Root cause takes hours. The post-mortem asks the same question: why didn't anyone catch this before we shipped?
No Pre-Deploy Risk Signal
Your CI/CD pipeline runs tests and lints code. It does not ask: what is the downstream blast radius of this change? That gap — between knowing the code works and knowing the system is safe — is where P1 incidents are born.
From Deployment Dread to Deployment Confidence. Four Steps.
Connect to Your Elasticsearch Cluster
Blast Radius reads your existing Elasticsearch observability data — logs, metrics, APM traces. No new agents. No new data pipeline. No new configuration to maintain.
Auto-Discover Your Live Service Topology
The accelerator builds a real-time dependency map from your actual data — not from documentation that's already out of date.
Simulate the Blast Radius of Your Change
Select the service or component you're about to deploy. Blast Radius runs a propagation simulation and returns a ranked list of every downstream service, scored high / medium / low risk.
Ship with Confidence — or Block High-Risk Deploys
Green scores ship. High-risk deployments trigger a configurable block via webhook — integrated directly into GitHub Actions, Jenkins, or CircleCI.
Elasticsearch data in → live topology map → blast radius simulation → CI/CD gate decision
Built for the Infrastructure Team That Ships Fast and Sleeps Well.
Pre-Deployment Impact Simulation
Model the downstream failure impact of any infrastructure or code change before it ships. Propagation analysis runs against your live dependency graph — not a static diagram.
At-Risk Service Scoring
Every service in the blast radius gets a risk score: high, medium, or low. Rankings factor in historical failure correlation, dependency depth, and upstream load patterns.
Live Topology Discovery
Blast Radius auto-discovers your service topology from existing APM traces and log data. Nothing to draw. Nothing to configure. Topology updates in real time as your services evolve.
CI/CD Pipeline Integration
Webhook-based integration with GitHub Actions, Jenkins, and CircleCI. Configurable thresholds block high-risk deployments automatically. Zero delay on passing deploys.
Historical Incident Correlation
Cross-references your incident history to identify services with previous failure sensitivity to the changed component. Pattern-matched risk, not just structural risk.
Configurable Deployment Blockers
Set your own risk threshold. High-risk deployments halt pending review. Engineering judgment stays in the loop — the pipeline just makes sure nothing slips through unchecked.
What Deploying with Blast Radius Actually Looks Like.
A VP Engineering at a mid-market SaaS company ran Blast Radius before a major infrastructure change. The simulation surfaced 12 at-risk services their team had not mapped. They addressed three before deployment and monitored the others. Zero P1 incidents followed. That's not luck — that's topology-aware deployment.
Read the Observability Consolidation case study →pre-deployment
in the first 30 days
avoided per deployment cycle
Blast Radius Doesn't Live Alone. It Lives in Your Stack.
Topology Builder builds and maintains the live service dependency map that Blast Radius runs simulations against. Run them together for a continuously updated blast radius model that reflects your architecture as it actually exists today, not as it existed last quarter.
Blast Radius sits at the center of the pre-deployment intelligence loop. It consumes topology data, runs impact simulations, scores downstream services, and gates the CI/CD pipeline — all from your existing Elasticsearch observability investment.
When a deployment does cause alerts — even a well-analyzed one — Alarm Noise Suppression filters the signal from the noise. Together, Blast Radius and Alarm Noise Suppression cover both sides of the deployment event: before and after.
All three accelerators are available individually or as part of the Observability Modernization Sprint engagement. No redundant tooling. No new data platforms.
Customer Testimonial
Blast Radius identified 12 at-risk services before we deployed. That alone saved us three weeks of post-launch firefighting — and spared my team the post-mortem that nobody wants to write after a Friday night incident.
Questions We Get Before the Demo.
Straight answers to the objections that actually matter. If something isn't covered here, ask in the demo — we'll answer it in the first five minutes.
24-hour response to all demo requests.
Your On-Call Team Deserves a Better Friday Night.
Fifteen minutes. We'll show you a live blast radius simulation on a topology like yours. No pitch deck. No commitment. Just the tool doing what it does.