What does AceMQ ELK Stack support include?

Our ELK Stack support covers 24/7 emergency incident response with a 15-minute SLA, root cause analysis on every P1, Logstash pipeline engineering, Beats and Elastic Agent fleet operations, index template and ILM design, Kibana dashboard performance work, and pipeline architecture reviews. Every ticket is handled by a named senior engineer assigned to your account — there is no tier-1 triage layer and no per-incident charge.

How does this differ from your Elasticsearch support?

This page covers the pipeline and visualisation layers — Logstash, Beats and Elastic Agent, ingest pipelines, index templates and ILM, and Kibana. Our Elasticsearch support covers the cluster layer: shard allocation, heap and GC, node failures, snapshot and restore, and query performance inside the engine. Most customers need both, and the same named engineers handle them so an incident is not split across two teams.

Why is Logstash saturating CPU when our event rate is not that high?

Nearly always a grok pattern. Grok compiles to regular expressions, and a pattern with nested quantifiers or greedy wildcards can backtrack catastrophically on a line that does not match — a single event can burn a core for seconds. We bisect the filter chain to identify the pattern, then rewrite it with anchored, non-greedy expressions, or replace it with dissect where the format is positional. Dissect is dramatically cheaper and covers more log formats than people expect.

Should we parse in Logstash or in Elasticsearch ingest pipelines?

It depends on what else the data needs. Ingest pipelines run on the cluster's ingest nodes and are simpler to operate, which suits straightforward parsing. Logstash is the right place when you need external enrichment lookups, complex conditional routing, buffering with a persistent queue, or outputs to systems other than Elasticsearch. The failure mode we see most is doing both — an estate that adopted Beats modules or Elastic Agent while keeping an older Logstash pipeline, and now parses everything twice.

Our Filebeat agents show as healthy but no data arrives. What causes that?

Three things account for most cases. The registry file has been corrupted or reset, so Beats has lost its position and its view of which files it has read. A log rotation happened in a way the harvester did not track, and it is holding a deleted inode. Or the host has more log files than harvester_limit allows, so some files are never picked up. The Beats log usually shows the harvester state clearly once you know which of the three to look for.

Can you help when a Kibana dashboard times out?

Yes, and the fix is usually in the dashboard rather than the cluster. The dominant cause is index patterns with broad wildcards that resolve every panel against hundreds or thousands of shards spanning years of data. Narrowing the pattern, adopting data streams, using runtime fields sparingly, and restructuring panels so they query only what they need typically brings load times down by an order of magnitude without adding a single node.

How is AceMQ ELK Stack support priced?

Support is priced as an annual contract based on your environment size, required SLA tier, and coverage hours — not per incident or per ticket. That means calling us during an outage never carries a cost decision. Contact us for a quote; we turn them around within 24 hours.

ELK Stack Support

24/7 ELK Stack Support with a 15-Minute Emergency SLA

AceMQ supports the ingest and visualisation layers of the Elastic Stack — Logstash pipelines under backpressure, grok patterns burning CPU, Beats that stop shipping, index templates and ILM policies that never applied, and Kibana dashboards that time out. For cluster-layer problems, see our Elasticsearch support. Every ticket reaches a named senior engineer.

Senior ELK Stack engineers on call right now — 24/7/365

15 min emergency SLA24 /7 global coverage130 + enterprise customers26 + countries served

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

Escalation Path

Your first hour of a ELK Stack 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 ELK Stack 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

ELK Stack problems we fix every week

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

Symptom you're seeingWhat we check firstTypical resolution

Logstash persistent queue growing on disk, events arriving late

What we check firstWhether the block is downstream or in the filter stage — output response times and the pipeline's filter duration from the node stats API. A persistent queue filling means the pipeline cannot drain as fast as it fills, and the queue is the symptom rather than the cause.

Typical resolution1–2 hours

Logstash pinning every CPU core with modest event throughput

What we check firstThe grok patterns in the filter chain for catastrophic backtracking. A pattern with nested quantifiers or greedy matches over a line that does not match can consume enormous CPU on a single event. We find the offending pattern by disabling filters in halves before rewriting it with anchors and dissect where possible.

Typical resolution2–4 hours

A Filebeat host stopped shipping but the service is running

What we check firstThe registry file and harvester state. A corrupted or reset registry, a file rotation the harvester lost track of, or hitting harvester_limit on a host with thousands of log files all produce a running agent that ships nothing.

Typical resolutionUnder 1 hour

Kibana dashboard times out or loads for minutes

What we check firstHow many indices each visualisation resolves against. A wildcard index pattern spanning years of daily indices forces every panel to query hundreds of shards. We count the resolved shards per panel before assuming the cluster is undersized.

Typical resolution1–2 hours

New indices have wrong field mappings — fields are text, not keyword

What we check firstIndex template priority and pattern match order against the index name actually created. A composable template that does not match, or a lower priority than a competing template, silently leaves dynamic mapping to guess the types.

Typical resolution1–3 hours

ILM is not rolling over indices — disk filling with hot data

What we check firstThe ILM explain output for the index. The usual causes are an index created without the rollover alias, a policy attached after creation, or a step erroring silently. The explain API names the step it is stuck on.

Typical resolution1–2 hours

Every document is being processed twice or enriched twice

What we check firstWhether an ingest pipeline on the Elasticsearch side is duplicating work already done in Logstash. Estates that adopted Elastic Agent or Beats modules alongside an existing Logstash pipeline commonly end up with both parsing the same events.

Typical resolution2–4 hours

Timestamps wrong — events appear hours off or all at ingest time

What we check firstThe date filter and its timezone handling against the source format, then whether @timestamp is being overwritten downstream. Logs without an explicit offset default to the processing node's timezone, which differs between your Logstash hosts and your laptop.

Typical resolutionSame day

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

Not on the list? Tell us what's breaking

Support In Practice

ELK Stack problems we've already solved

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

All use cases

Remediation

ELK Stack Logstash Back-Pressure Remediation

Energy Utility Operator

Remediation of an ELK pipeline where Logstash back-pressure stalled Beats agents and left log gaps across the fleet.

ELK StackLogstashElasticsearch

Read case study

Support

ELK Stack Pipeline and Ingest Support

Global Logistics Provider

Ongoing support across the full ELK ingest path — Beats, Logstash, ingest pipelines, and index templates — with 24/7 coverage.

ELK StackLogstashElasticsearch

Read case study

Assessment

ELK Stack Log Volume and Retention Assessment

Insurance Services Provider

Assessment of log volume, field-level utility, and retention across an ELK estate where storage growth had outpaced any plan for it.

ELK StackElasticsearchKibana

Read case study

What's Included

Everything in your ELK Stack support contract

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

Emergency Incident Response

Ingest stalled, queues filling, dashboards down, or shippers silently not delivering. A senior engineer joins a live bridge within 15 minutes with access to diagnose — not a ticket acknowledgement.

Logstash Pipeline Engineering

Filter chain profiling, grok rewrite and dissect migration, worker and batch sizing, persistent queue configuration, and multi-pipeline design so one noisy source cannot stall every other input.

Beats & Agent Fleet Operations

Filebeat, Metricbeat, and Elastic Agent deployment at scale — registry and harvester behaviour, module configuration, backpressure handling, and fleet policy management across large host estates.

Index Templates, Mappings & ILM

Composable template design and priority, mapping and field type control, data stream adoption, and ILM policies that actually roll over — so retention and storage behave the way the policy says they do.

Kibana Dashboard Performance

Index pattern scoping, panel query cost, runtime field usage, and dashboard design that resolves against the indices it needs rather than every index you have ever created.

Pipeline Architecture & Migration

Deciding what belongs in Logstash, in Elasticsearch ingest pipelines, or at the edge in Beats — plus buffering with Kafka or Redis in front of Logstash, and migration off ELK where that is the right call.

Anywhere You Run It

We support ELK Stack wherever it's deployed

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

Logstash 7.x & 8.xFilebeat, Metricbeat & Elastic AgentKibana 7.x & 8.xElastic CloudSelf-managed Elastic StackKubernetes & OpenShift (ECK)AWS (EC2, EKS)Microsoft Azure (AKS)Google Cloud (GKE)Kafka or Redis buffered pipelinesBare metal & on-premiseAir-gapped / no outbound access

Why AceMQ

What you get that you don't get elsewhere

We Fix the Pipeline, Not Just the Cluster

Most ELK pain lives before the data lands — grok cost, queue backpressure, shippers that stop, mappings applied too late. That is the layer we work at, alongside our Elasticsearch cluster support when the problem is downstream.

Named Engineers, Zero Cold Start

The same senior engineers stay on your account. They know your pipelines, your sourcetypes, and your index layout — so a P1 call starts with diagnosis, not twenty minutes of you explaining your ingest path.

No Tier-1 Triage Layer

You reach a senior engineer directly by phone, email, or Slack. No help desk collecting information to pass along, and no escalation approval standing between you and someone who can actually fix it.

Deep on the Buffer in Front of Logstash

Serious ELK pipelines put Kafka or Redis between the shippers and Logstash. Messaging is our core discipline, so partitioning, consumer lag, retention, and replay are home ground rather than adjacent knowledge.

Genuine Follow-the-Sun Coverage

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

Proactive, Not Just Reactive

Quarterly reviews of ingest volume, pipeline CPU cost, mapping explosion risk, and ILM effectiveness — plus alerts on version-specific issues affecting the exact releases you run.

FAQ

ELK Stack support questions

A Stalled Pipeline Means Nobody Can See the Outage

Whether you need emergency response tonight or a support contract that keeps ingest, mappings, and dashboards healthy, AceMQ staffs every engagement with a named senior 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

Prefer to talk now? Call us directly or use the consultation tab to find a time that works.