Prometheus Support

24/7 Prometheus Support with a 15-Minute Emergency SLA

AceMQ supports Prometheus as production infrastructure — the OOM kill that turns into a two-hour WAL replay, the label somebody added last Tuesday that quadrupled your series count, targets silently dropped by a relabel rule, and Thanos queries that time out over anything longer than a week. Every ticket reaches a named senior engineer.

Senior Prometheus engineers on call right now — 24/7/365
15 min emergency SLA24 /7 global coverage130 + enterprise customers26 + countries served

Trusted for mission-critical Prometheus by teams in finance, healthcare, defense, and telecom

Escalation Path

Your first hour of a Prometheus outage

Most vendors publish an SLA number. This is what actually happens, minute by minute, when you page a senior AceMQ engineer.

T+0

You page us

Phone, email, or Slack — any channel reaches the on-call senior engineer directly. No web form, no tier-1 queue.

T+15

Named engineer live

A senior engineer who already knows your environment joins a live bridge. Zero cold-start, no re-explaining your topology.

T+30

Root cause isolated

Direct broker access, log and metric review, and a working hypothesis with a rollback plan before we touch anything.

Post

Written RCA

Documented root cause, the fix applied, and the prevention steps — delivered after every P1, not just when asked.

Response Times

SLA tiers, contractually guaranteed

Every tier reaches a senior Prometheus engineer. There is no tier-1 triage layer to get through.

P1 — Emergency
15 min

Production down, messages not flowing, cluster or broker failure

P2 — Critical
1 hour

Severe degradation, rising error rates, approaching capacity limits

P3 — High
4 hours

Performance issues, configuration problems, non-critical failures

P4 — Standard
Next day

Questions, guidance, best practices, non-urgent improvements

Incident Triage

Prometheus problems we fix every week

These are real symptoms from real Prometheus production environments — and the first thing our engineers check when one comes in.

Prometheus OOM-killed, then unavailable for an hour or more on restart
What we check firstActive series count and its recent growth, via the TSDB status endpoint and topk on scrape_samples_scraped. A new label carrying user IDs, request IDs, or full URL paths is the single most common cause, and the long restart is WAL replay working through everything that label created.
Typical resolution1–2 hours
WAL replay taking hours after every restart
What we check firstWAL segment count and size against head series. Replay is single-threaded per block and scales with head series, so it is a cardinality symptom rather than a disk symptom — the fix is fewer series, not faster storage.
Typical resolution2–4 hours
Targets missing from the scrape pool with no error anywhere
What we check firstThe service discovery page before the targets page. A relabel_configs rule with a keep or drop action that no longer matches after a label rename silently removes targets, and nothing logs it because dropping is the intended behaviour.
Typical resolutionUnder 1 hour
Grafana dashboards slow, but only the ones with long time ranges
What we check firstSeries touched per query, then whether recording rules exist for the expensive expressions. A rate over a sum over an unaggregated metric re-evaluates every series on every refresh; a recording rule computes it once per evaluation interval.
Typical resolution1–3 hours
Alerts fire but nobody gets paged
What we check firstAlertmanager routing tree and active silences. Alerts routinely match a catch-all receiver higher in the tree than intended, get suppressed by an inhibit_rule written for a different scenario, or land under a silence somebody created during last month's maintenance and never expired.
Typical resolutionUnder 1 hour
Thanos or Mimir queries time out over anything beyond a few days
What we check firstWhether compaction and downsampling have actually run for that time range. Querying raw blocks for a 30-day window fans out across every store gateway; the 5m and 1h downsampled series exist precisely to avoid that, and they are frequently missing because the compactor has been failing quietly.
Typical resolutionSame day
Disk filling faster than the retention setting predicted
What we check firstBytes per sample against series churn. Retention bounds time, not size, so churn — pods that restart constantly, each producing a fresh set of series — inflates storage well past a sizing estimate based on steady-state series count.
Typical resolution1–2 hours
remote_write backing up, with samples dropped at the queue
What we check firstThe remote write queue metrics — shards, pending samples, and failed sends — against the receiving endpoint's latency. Under-provisioned max_shards and a slow remote endpoint produce backpressure that Prometheus resolves by discarding samples.
Typical resolution1–3 hours

Resolution times reflect typical Prometheus engagements under an active AceMQ support contract. Every P1 closes with a written root-cause analysis.

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Support In Practice

Prometheus problems we've already solved

Representative engagements showing how these incidents get diagnosed and closed under an AceMQ support contract.

Assessment

Stabilizing RabbitMQ on Kubernetes for Mission-Critical Airport Systems

Global Aviation Technology Provider

Troubleshooting cluster failover, partition handling, and quorum queue issues in a high-stakes aviation operational environment.

RabbitMQKubernetesQuorum Queues
Read case study
Remediation

RabbitMQ Performance Remediation for Telecom-Scale IoT

Global Telecom Leader

Resolving weekly RabbitMQ crashes, optimizing for 300,000+ connected devices, and architecting horizontal scaling strategy.

RabbitMQKubernetesQuorum Queues
Read case study
Remediation

Grafana Outage and Datasource Timeout Remediation

Telecommunications Operator

Remediation of a Grafana deployment that became unusable during incidents, with dashboards timing out exactly when engineers needed them most.

GrafanaPrometheusKubernetes
Read case study
Support

Grafana Alerting and Datasource Support

Energy Utility Operator

Ongoing support for Grafana unified alerting, notification routing, and datasource reliability across an operational monitoring estate.

GrafanaPrometheusAlertmanager
Read case study
Assessment

Grafana Dashboard Estate Assessment

Global Logistics Provider

Assessment of a sprawling Grafana dashboard estate to identify duplication, broken panels, and the small set of dashboards anyone actually uses.

GrafanaPrometheusAmazon S3
Read case study
Remediation

Prometheus Cardinality Explosion and OOM Remediation

Digital Commerce Platform

Emergency remediation of Prometheus servers being OOM-killed repeatedly after a deployment introduced an unbounded label.

PrometheusKubernetesGrafana
Read case study
Support

Prometheus Restart and WAL Replay Support

Global Payments Processor

Ongoing support for large Prometheus instances where restarts caused extended monitoring blind spots due to slow write-ahead log replay.

PrometheusThanosKubernetes
Read case study
Assessment

Prometheus Scrape and Federation Architecture Assessment

Industrial Automation Manufacturer

Assessment of a Prometheus federation topology that had grown past its limits, causing gaps and duplicated data across sites.

PrometheusGrafanaKubernetes
Read case study
What's Included

Everything in your Prometheus support contract

No add-on pricing for incidents. No per-ticket charges. One contract covers the whole surface.

Emergency Incident Response

Prometheus down, alerting silent, or a server stuck in WAL replay while your on-call is blind. A senior engineer joins a live bridge within 15 minutes — monitoring being down during an incident is a P1 on its own.

Cardinality Control

Finding the metric and label that caused the growth, dropping it at the right layer with metric_relabel_configs, and putting guardrails in the exporter or instrumentation so the next well-meaning commit does not repeat it.

PromQL & Recording Rule Tuning

Rewriting queries that scan too many series, building the recording rules your dashboards should have had, and setting evaluation intervals that keep rule groups finishing well inside their window.

Alertmanager Design

Routing trees, grouping, inhibition, silences, and high-availability Alertmanager clusters. We prune alerts that never led to action and make sure the ones that survive reach the right team once.

Long-Term Storage Architecture

Thanos, Mimir, and Cortex — sidecar versus receive, compactor and downsampling health, object store layout, and query fan-out. We fix the compaction failures that make historical queries slow long before anyone notices.

Federation, Sharding & Scale

When to shard by scrape target rather than federate, how to keep hierarchical federation from becoming a single point of failure, and remote_write tuning for multi-cluster and multi-region estates.

Anywhere You Run It

We support Prometheus wherever it's deployed

Cloud, Kubernetes, bare metal, hybrid, and air-gapped — including environments where you can't give us outbound network access.

Kubernetes (Prometheus Operator, kube-prometheus-stack)OpenShift monitoring stackAWS (EC2, EKS, Amazon Managed Prometheus)Microsoft Azure (AKS, Azure Monitor managed)Google Cloud (GKE, Google Managed Prometheus)Thanos, Mimir & CortexVictoriaMetricsVMware vSphere & TanzuBare metal & on-premiseAir-gapped / no outbound accessAlertmanager HA clustersGrafana Cloud remote_write
Why AceMQ

What you get that you don't get elsewhere

Named Engineers, Zero Cold Start

The same senior engineers stay on your account. They know your scrape topology, your series budget, and your alert routing — so a P1 call opens with diagnosis instead of you describing the setup.

No Tier-1 Triage Layer

You reach a senior engineer directly by phone, email, or Slack. Nobody collects details to pass along, and there is no escalation approval standing between you and the person who can fix it.

Cardinality Is the Job, Not a Footnote

Most Prometheus incidents are one metric with one bad label. We find it fast, drop it at the correct layer, and fix the instrumentation — rather than doubling the memory limit and waiting for the same page in six weeks.

The Whole Stack, Including Grafana

Prometheus almost never runs alone. We support the Grafana on top, the Thanos or Mimir behind it, the exporters feeding it, and the Kubernetes underneath — so nothing gets handed back as somebody else's layer.

Genuine Follow-the-Sun Coverage

Engineers across 26+ countries and every time zone. Your 3am page is someone's mid-afternoon — no overnight skeleton crew, no waiting for a region to come online.

Proactive, Not Just Reactive

Quarterly reviews of series growth, rule evaluation timing, and storage headroom, so you resize ahead of the OOM rather than during it. Cardinality problems announce themselves weeks before they page anyone.

FAQ

Prometheus support questions

Monitoring That Fails During an Incident Makes Every Incident Longer

Whether you need emergency response tonight or a support contract that keeps cardinality and alert noise under control, AceMQ staffs every engagement with a named senior Prometheus engineer. Support quotes returned within 24 hours.

Get in Touch

Talk to a Support Expert

Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.

305-204-2607
info@acemq.com
66 W. Flagler St. 9th Floor
Miami, FL 33130

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