MongoDB Consulting & Support

MongoDB Consulting & Support for Enterprises

AceMQ engineers design and operate MongoDB deployments that outgrew a spreadsheet-shaped schema years ago — sharded clusters, multi-region replica sets, and the relational-to-document migrations that got them there. Every engagement is staffed by a named senior engineer, not a ticket queue.

A senior engineer, not an SDR. No sales sequence attached.

Senior SMEs
11+
Emergency SLA
<15min
Customers
160+
Countries Served
26+

Without redesigning your document model from scratch or moving to another databaseFor production incident cover, see AceMQ MongoDB 24/7 support.

Customers

  • Microsoft
  • Henry Schein
  • Enbridge
  • Gojek

Partners

  • Broadcom
  • Redis
  • VMware Tanzu
  • OSSeva

The Problem

Why teams call us about MongoDB

Eight MongoDB problems teams bring to AceMQ, from a working set that outgrew the WiredTiger cache and a shard key that sends every insert to one shard, to elections slower than the driver timeout. If one describes your week, that is where the review starts.

  1. 01

    The working set stopped fitting in RAM and page faults now show up as application latency

  2. 02

    A shard key chosen early sends most of the traffic to one shard and the balancer never catches up

  3. 03

    Documents with unbounded arrays are creeping towards the 16MB ceiling

  4. 04

    COLLSCAN keeps appearing in the slow query log for a collection everyone believed was indexed

  5. 05

    Replica set elections take longer than the driver timeout, so writes fail during failover

  6. 06

    Index size has passed data size and nobody can say which indexes are safe to drop

  7. 07

    The oplog window is now shorter than the time a secondary needs to catch up after maintenance

  8. 08

    The Atlas bill grows every quarter and the cluster tier was last sized by someone who has left

A good fit if you run MongoDB in production, on Atlas, Enterprise Advanced or self-managed Community, and want senior engineers who stay on a problem until the root cause is written down.

Not a fit for small teams with non-critical workloads. AceMQ is not a budget consultancy: we work with enterprises running business-critical and compliance-heavy MongoDB.

Running MongoDB in production? Get a quote from a senior engineer, answered within one hour.

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How it breaks, and the fix

What happens to your writes when the MongoDB primary steps down?

A write acknowledged by the primary alone, with w:1, may not have reached any secondary yet. If the primary fails first, a secondary is elected without that write, and the old primary rolls it back when it rejoins. The write concern decides whether that can happen.

Primary failure in a three-member replica set

Application, driver, one primary, two secondaries

Illustrative

  1. The driver writes to the primary. Both secondaries tail the oplog and stay a second or two behind, so a secondary read is nearly current.

  2. The primary fails. Secondary 1, far behind on oplog apply, wins the election. Writes that only the old primary held are rolled back when it rejoins, and the application never saw an error.

  3. Writes use w: majority, so an acknowledged write is already on most members. The caught-up secondary 2 takes over with every acknowledged write intact, and the driver finds the new primary on its own.

Lost writes after an election are one of the reasons teams call AceMQ about MongoDB. The fix is configuration and design: w: majority for writes that must survive, retryable writes with a driver that follows the topology, a secondary kept close to the primary by fixing the slow disk or the bulk load that makes it lag, an oplog window longer than your longest maintenance event, and an election drill run in staging first. Atlas elects the same way, so the write concern stays yours to set.

Our Services

MongoDB Consulting & Services

AceMQ runs five MongoDB service lines: schema and architecture design, performance tuning, migration to and from MongoDB, managed operations with 24/7 support, and a structured health check. A named senior engineer leads each one, and any of them can roll into 24/7 support with a 15-minute emergency SLA.

  • 01

    MongoDB Schema & Architecture Design

    We design document models around your actual access patterns instead of copying a relational schema into JSON. Every design decision — embed or reference, shard key, replica topology — is made against your read/write ratio and growth curve.

    • Embedding vs. referencing decisions based on access patterns and document growth
    • Avoiding unbounded arrays and the 16MB document size ceiling
    • Shard key selection to prevent hot-partition write concentration
    • Replica set topology design for read preference and write concern requirements
  • 02

    Performance Tuning & Query Optimization

    When query latency creeps up without an obvious cause, we go straight to the index plan, the working set, and the WiredTiger cache — not generic tuning checklists.

    • Index strategy: compound indexes, covered queries, and index intersection analysis
    • WiredTiger cache sizing and eviction pressure diagnosis
    • Aggregation pipeline optimization and $lookup elimination
    • Slow query analysis via Atlas Performance Advisor or the self-hosted database profiler
  • 03

    Migration to and from MongoDB

    Most MongoDB migrations we run fall into two buckets: teams that started relational and outgrew the join-heavy schema, or teams moving between self-managed and Atlas for cost or control. We've run both directions.

    • Relational-to-document schema remodeling from Oracle, SQL Server, or PostgreSQL
    • Self-managed MongoDB to Atlas migration, and the reverse for cost control
    • Zero-downtime version upgrades across major release lines
    • Workload evaluation against Apache Cassandra when write throughput favors a wide-column model
  • 04

    Managed Operations & 24/7 Support

    Sharded clusters and multi-region replica sets don't fail cleanly — they degrade. Our engineers monitor the signals that predict trouble and respond in minutes when it happens anyway.

    • Replica set failover monitoring and oplog window sizing
    • Sharded cluster balancer tuning and chunk migration scheduling
    • Backup and restore validation with point-in-time recovery testing
    • 24/7 incident response for replication lag and connection storms
  • 05

    MongoDB Health Check & Assessment

    A structured review of your cluster's index usage, working set fit, and security posture — delivered as a written report your team can act on, not a slide deck.

    • Index usage audit against $indexStats to find unused and duplicate indexes
    • Working-set-versus-RAM analysis to catch premature cache eviction
    • Security posture review: authentication, encryption at rest, network exposure
    • Written report with prioritized remediation ranked by production risk
  • 15 MIN SLA

    24/7 MongoDB Support

    Named senior engineers on your account — 15-minute emergency response, no ticket routing, no junior triage.

    • 15-minute emergency response SLA
    • Named engineer, zero cold-start
    • Proactive CVE & health monitoring
    • Quarterly deployment reviews
    Compare the four MongoDB support tiers

Want AceMQ to take this off your team's plate? Tell us about your MongoDB estate.

Contact Us

24/7 Support

MongoDB Support When It Matters Most

AceMQ MongoDB support gives you a named senior engineer and a 15-minute first response when production is down, 24/7, on Atlas, Enterprise Advanced or self-managed Community. Lower severities get 1-hour, 4-hour and next-day responses, and every P1 ends with a written root-cause analysis.

  1. 15 minfirst responseEmergencyProduction down, messages not flowing, queue manager failure
  2. 1 hourfirst responseCriticalSevere degradation, high error rates, approaching capacity
  3. 4 hoursfirst responseHighPerformance issues, configuration problems, non-critical failures
  4. Next Dayfirst responseStandardQuestions, guidance, best practices, non-urgent improvements

P1 escalation path

A replay of one P1, from the first page to the written root-cause analysis

SLA 15:00
T+Elapsed15:00
Engineer on your bridge

15-minute P1 response, 24/7.
A response time, not a resolution time.

  1. T+00:00

    P1 opened, on-call engineer paged

    Phone, email or Slack reaches the on-call senior engineer directly, whether the incident is in RabbitMQ, Kafka, Redis, PostgreSQL or Kubernetes. No web form, no tier-1 queue.

    Paged
  2. T+15:00

    Senior engineer on your bridge

    A senior engineer who already knows your environment joins a live bridge, so nobody has to re-explain your topology.

    Live
  3. T+30:00

    Specialists across the stack join

    When an incident crosses components, the engineers who know each one join. For RabbitMQ, the path runs to the core team.

    If needed
  4. After

    Written root-cause analysis

    Root cause, the fix applied and the prevention steps, delivered after every P1.

    Every P1

How Our Support Actually Works

Beyond SLAs — the model behind senior-only, zero-cold-start expert access.

  • Named Engineers on Your Account

    Every ticket is handled by a senior SME assigned to your account — not a pool of anonymous agents. Zero cold-start. No re-explaining your environment.

  • Live Escalation on Any Ticket

    Any ticket can be escalated to a live session with your named engineer via calendar booking. No gatekeeping, no approval required — direct access, always.

  • Proactive Risk Mitigation

    Quarterly health checks on your deployment plus shared intelligence from 50+ support customers — we surface risks before they reach production.

  • Critical Bug & CVE Intelligence

    Proactive alerts on critical bugs and CVEs affecting your exact version, with version compliance monitoring so you're never caught off guard.

  • Commercial EOL Versions

    Commercial support for end-of-life MongoDB versions, with security fixes backported through OSSeva, so the upgrade happens on your schedule rather than the community's.

Compare MongoDB support plans

How It Works

What actually happens next

An AceMQ MongoDB engagement runs in four stages: a cluster and schema review of 1 to 2 weeks, written findings within a week, changes made alongside your team as rolling operations so the replica set keeps serving, then a handover with runbooks for elections, secondary resync and restore drills.

1–2 weeks

Cluster and schema review

We examine the document model against the access patterns actually hitting it, shard key distribution, index usage from the profiler, oplog window, and how the replica set behaves during an election — not just the Atlas or Ops Manager dashboard.

Within a week

Written findings and plan

Which queries and which documents are causing the symptom, which indexes earn their storage, and what to change first. Sized for your own engineering leadership to sign off.

Scoped per engagement

Implementation alongside your team

Index builds, shard key changes and version upgrades staged as rolling operations, so the replica set keeps serving reads and writes throughout.

Ongoing

Handover and optional cover

Runbooks for your topology — election behaviour, secondary resync, restore drill — plus 24/7 support with a 15-minute emergency SLA if you want it.

  • Written findings before any change
  • Index builds and upgrades staged as rolling operations
  • Your engineers in the room
  • You keep the runbooks
  • Ad hoc engagements or an annual partnership

A senior engineer, not an SDR. No sales sequence attached.

Customer Success

Real MongoDB Results

AceMQ case studies where MongoDB was part of the estate, from WiredTiger cache eviction and oplog window sizing to sharding strategy. Each one links to the full write-up: the environment, what AceMQ assessed or changed, and the result.

1 / 4 case studies

  • Remediation

    MongoDB WiredTiger Cache Eviction Remediation

    Global Payments Processor

    Diagnosing and resolving application stalls caused by a working set that outgrew the WiredTiger cache, pushing the server into continuous eviction pressure.

    MongoDBKubernetesPrometheusLinux
    Read case study : MongoDB WiredTiger Cache Eviction Remediation
  • Support

    MongoDB Replica Set and Oplog Window Support

    Healthcare Analytics Provider

    Ongoing support for replica sets where a short oplog window was forcing repeated full initial syncs of secondaries during nightly batch loads.

    MongoDBKubernetesTerraformPrometheus
    Read case study : MongoDB Replica Set and Oplog Window Support
  • Consulting

    MongoDB Sharding Strategy and Shard Key Redesign

    Logistics and Freight Technology Provider

    Redesigning a monotonically increasing shard key that concentrated all inserts on one shard and produced jumbo chunks that would not split.

    MongoDBKubernetesKafkaTerraform
    Read case study : MongoDB Sharding Strategy and Shard Key Redesign
  • Assessment

    MongoDB Deployment Health Assessment

    Public Sector Agency

    Structured review of schema design, index efficiency, replica set topology, and backup recoverability ahead of a major workload increase.

    MongoDBLinuxPrometheusKubernetes
    Read case study : MongoDB Deployment Health Assessment
All use cases

Solutions

Every way AceMQ works with MongoDB.

AceMQ covers MongoDB end to end: consulting and upgrades, 24/7 support and incident management, proactive monitoring, managed MongoDB on your infrastructure or on AceMQ's, OSSeva patches for MongoDB 4.2 to 6.0, and a fixed-price health check.

Projects

Build, fix or move MongoDB

Fixed-scope work led by a senior engineer: architecture and new builds, a health check of what you run today, or a migration with a reversible cutover.

Support and managed services

Keep MongoDB running

Four tiers of ongoing cover once you are live. Each tier hands more of the day-to-day work to AceMQ, from a 15-minute emergency SLA to AceMQ hosting and running MongoDB for you.

Compare the four MongoDB support tiers

Side by side

Atlas or self-managed MongoDB: what do you still own?

MongoDB Atlas runs the servers for you: provisioning, patching, backups and failover. Self-managed MongoDB leaves all of that with your team. Either way, document design, shard keys, indexes, working set sizing and write concern stay with you, and that is the layer AceMQ covers.

MongoDB Atlas compared with self-managed MongoDB on who runs the servers, versions and settings, end of life, incidents, cost shape and exit
QuestionMongoDB AtlasSelf-managed (Community or Enterprise Advanced)
Who runs backups, patching and failover?MongoDB, for the cluster. Backups, minor upgrades and elections are handled for you.Your team, or a specialist on call. Ops Manager automates much of it for Enterprise Advanced.
Which versions and settings can you use?The versions and settings Atlas exposes for your tier. Some server parameters and OS-level tuning are not available.Any supported version and setting, including OS and filesystem tuning, and custom builds such as Percona Server for MongoDB.
What happens at end of life?Atlas upgrades clusters that reach end of life, on MongoDB's schedule, so the application has to be ready by then.You choose the date. Community stops getting upstream fixes at end of life, and OSSeva patched builds can extend MongoDB 4.2 to 6.0.
Who answers a database incident?MongoDB support runs the platform. Index design, shard keys, working set size and connection pools stay with your team.Your team, or AceMQ: a named senior engineer, 24/7, a 15-minute emergency response and a written root-cause analysis for every P1.
What does it cost?Cluster tier, storage, backup, data transfer and add-ons such as Atlas Search on the Atlas invoice. The bill grows with tier and data.Your own infrastructure, plus a support contract priced on the cover you need.
How do you leave?mongodump or a live migration to another cluster. Atlas-only features, such as Atlas Search, do not travel.Nothing to exit. Runbooks and topology documentation are yours.

For what MongoDB, Inc., the community and independent support each cover, see MongoDB support options compared. For version dates, read MongoDB end-of-life dates by version.

Not sure which option fits? A senior MongoDB engineer will scope it with you.

Contact Us

One partner, not five

We Support Your Entire Tech Stack

MongoDB rarely fails in isolation. AceMQ covers the full surrounding infrastructure — so one team owns the whole path instead of pointing at each other.

Messaging & Streaming

Databases & Caching

Search & Analytics

Lakehouse & Compute

Observability & Monitoring

Data Integration

Cloud & Containers

API Management

VMware Tanzu

See all 51 technologies we supportShow fewer

Guides, articles and comparisons

Go deeper on MongoDB.

Guides from AceMQ engineers on MongoDB end of life, support options, backup and migration, plus the AceMQ services for the databases and systems that usually run next to MongoDB. Each link goes to the full article or service page.

Related services

Ready to talk MongoDB? Get a quote or send us a message.

Contact Us

FAQs

MongoDB Questions Answered

Eight answers on MongoDB from AceMQ: who answers when a cluster fails, supported and end-of-life versions, what consulting includes, Atlas or self-managed, slowdowns with no slow query, fixing a shard key, health checks, and working with your in-house team.

Still have questions about MongoDB? Email an Expert

Who answers when a MongoDB cluster fails in production, and how fast?

A named AceMQ senior engineer answers within 15 minutes, 24/7, when a MongoDB primary is down, a replica set has lost quorum or writes are failing, on Atlas, Enterprise Advanced or self-managed Community. Lower severities get a first response within 1 hour, 4 hours or the next business day, and every P1 ends with a written root-cause analysis.

Which MongoDB versions are still supported, and what happens after end of life?

MongoDB 6.0 reached end of life on 31 July 2025, 7.0 runs to 31 August 2027, 8.0 to 31 October 2029 and 9.0 to 31 October 2031, according to MongoDB's lifecycle schedule. AceMQ supports current lines 24/7, and patched builds through OSSeva keep self-managed Community 4.2, 4.4, 5.0 and 6.0 secure past end of life while the upgrade is planned.

What does MongoDB consulting from AceMQ include?

Our MongoDB consulting covers document and schema design, shard key selection, replica set topology, index strategy, WiredTiger and query tuning, version upgrades, and migration to or from MongoDB. A named senior engineer leads each engagement, delivers written findings before changing anything, and works alongside your team.

Atlas or self-managed MongoDB: how do you decide?

It depends on your team's operational capacity, compliance rules and cost at your data volume, not on a default. We compare Atlas and self-managed against your workload, including tier IOPS limits, backup needs and the Atlas bill, and give a recommendation with the trade-offs stated. We have moved clusters in both directions.

Our MongoDB cluster is slow but no single query looks slow. What is wrong?

This usually means the working set has outgrown the WiredTiger cache, so eviction now runs on application threads and slows every operation. Per-query profiling shows nothing dramatic because the pressure is spread out. We check cache and eviction metrics, index size against RAM and the profiler in aggregate, then fix it with index consolidation, schema changes or sizing.

Can a bad shard key be fixed without downtime?

Often, yes. MongoDB 5.0 and later can reshard a collection online, which covers many cases. Where that is not viable, for very large collections or older versions, we plan a dual-write and backfill into a correctly keyed collection with a validated cutover. We also tell you when the existing key is survivable and the migration is not worth the risk.

What is involved in a MongoDB health check?

A MongoDB health check reviews index usage from $indexStats, working set against RAM, shard balance and chunk distribution, oplog window, replica set configuration and security settings. You get a written report with prioritised fixes ranked by production risk. It is a fixed-price engagement, and many teams repeat it quarterly or after major changes.

How does a MongoDB consultant from AceMQ work with our in-house team?

Your engineers stay in the room. We share findings in writing before any change, make changes alongside your DBAs, and hand over runbooks for elections, secondary resync and restore drills so your team can repeat the work. Some teams keep AceMQ as escalation cover afterwards, and others only call us for upgrades.

Can we work with AceMQ on MongoDB without a long contract?

Yes. AceMQ works on MongoDB in two ways: ad hoc engagements for a defined piece of work, such as a health check, an upgrade or an incident, or an annual partner engagement that covers 24/7 support, proactive reviews and named engineers. Many teams start ad hoc and move to an annual partnership once the first engagement is done.

How much does AceMQ MongoDB support or consulting cost?

Every AceMQ proposal is tailored to your requirements: your MongoDB environment, the SLA you need, the hours of cover and the scope of work. Most contracts run $24,000–72,000 a year, depending on the SLA, the scope and how MongoDB is deployed, with aggressive discounts when several technologies share one contract. Request a quote and AceMQ replies within 1 hour.

Let's talk

Ready to Stabilize Your MongoDB Environment?

Whether you need emergency support, a healthcheck, a migration partner, or ongoing managed support — AceMQ staffs every engagement with a named senior MongoDB engineer. Quote requests answered within 1 hour.

A senior MongoDB engineer, not a sales queueAbout your clusters, not a pitch deckQuote requests answered within 1 hour

Production incident right now?Email a MongoDB Architect

Get in Touch

Talk to a MongoDB Expert

Send us a message and we'll follow up within 1 hour — 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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