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Testimonials
Good consultants execute on task and deliver as planned. Better consultants overdeliver on their tasks. Great consultants become full technology partners and provide expertise beyond their scope.
I am happy to call MeteorOps my technology partners as they overdelivered, provide high-level expertise and I recommend their services as a very happy customer.
We were impressed with their commitment to the project.
I was impressed at how quickly they were able to handle new tasks at a high quality and value.
I was impressed with the amount of professionalism, communication, and speed of delivery.
They are very knowledgeable in their area of expertise.
You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
Nguyen is a champ. He's fast and has great communication. Well done!
Working with MeteorOps was exactly the solution we looked for. We met a professional, involved, problem solving DevOps team, that gave us an impact in a short term period.
Thanks to MeteorOps, infrastructure changes have been completed without any errors. They provide excellent ideas, manage tasks efficiently, and deliver on time. They communicate through virtual meetings, email, and a messaging app. Overall, their experience in Kubernetes and AWS is impressive.
They have been great at adjusting and improving as we have worked together.
We got to meet Michael from MeteorOps through one of our employees. We needed DevOps help and guidance and Michael and the team provided all of it from the very beginning. They did everything from dev support to infrastructure design and configuration to helping during Production incidents like any one of our own employees. They actually became an integral part of our organization which says a lot about their personal attitude and dedication.
From my experience, working with MeteorOps brings high value to any company at almost any stage. They are uncompromising professionals, who achieve their goal no matter what.
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Free Project Planning: We dive into your goals and current state to prepare before a kickoff.
Pay-as-you-go: Use our capacity when you need it, none of that retainer nonsense.
Experts On-Demand: Get new experts from our team when you need specific knowledge or consultation.
We Don't Sleep: Just kidding we do sleep, but we can flexibly hop on calls when you need.
Ad-hoc Calls: When a video call works better than a chat, we hop on a call together.
How it works?
Grafana Mimir is a horizontally scalable, multi-tenant time series database for storing and querying Prometheus metrics across large environments. It is commonly used by platform engineering and SRE teams that need centralized metrics retention and consistent query performance for many clusters, services, or internal tenants, especially when standalone Prometheus becomes difficult to operate for long-term storage and high-ingest workloads.
Mimir is often deployed in Kubernetes and paired with object storage for cost-effective retention, while keeping compatibility with PromQL and Grafana dashboards. It adds operational controls that help standardize how metrics are ingested, isolated, and queried in shared observability platforms. For product details, see Grafana Mimir.
- Prometheus-compatible ingestion via remote_write and querying with PromQL
- Horizontal scaling for high ingestion rates and concurrent queries
- Multi-tenancy and isolation for teams, services, or customers
- Long-term retention backed by object storage
- Configurable limits and replication patterns to support reliability
Monitoring allows for a continuous data stream of system status and insights to be arranged in a user-friendly method that is easy to interpret.
- Provides real-time visibility into system performance and health, enabling proactive issue resolution.
- Alerts to potential problems before they escalate, reducing downtime and improving service reliability.
- Tracks and analyzes key performance indicators (KPIs), aiding in informed decision-making.
- Enhances security by detecting unusual activities or breaches, allowing for immediate response.
- Facilitates resource optimization by identifying underutilized or overburdened assets.
- Supports compliance efforts by maintaining logs and records of system activities.
- Enables a data-driven approach to IT management, improving overall operational efficiency.
Grafana Mimir is a horizontally scalable, multi-tenant time series database for storing and querying Prometheus metrics across large environments. It is commonly used to centralize metrics when single-Prometheus retention, query performance, or operational isolation becomes a constraint.
- Scales ingestion horizontally to handle high scrape volume and sustained remote_write throughput without relying on a single Prometheus instance.
- Supports Prometheus-compatible remote_write and query APIs, enabling long-term retention and centralized querying with minimal changes to existing tooling.
- Provides multi-tenancy with tenant-level isolation, making it suitable for shared observability platforms across teams, clusters, or customer environments.
- Uses object storage for durable long-term data, reducing reliance on large local disks and improving resilience for historical metrics.
- Offers high availability patterns for ingest and query components, helping maintain monitoring continuity during node, zone, or rolling upgrade events.
- Enables efficient querying over long time ranges, improving dashboard responsiveness and alert evaluations for extended retention periods.
- Centralizes metrics across multiple Kubernetes clusters and regions, simplifying consistent dashboards and alert rules across fleets.
- Includes operational controls for retention and compaction, supporting cost and performance tuning as data volume and cardinality grow.
- Integrates cleanly with Grafana and the Prometheus ecosystem, aligning with common workflows for dashboards, alerting, and incident response.
Grafana Mimir is a strong fit for platform and SRE teams building a centralized metrics layer with governance requirements and predictable scaling. It adds operational complexity compared to running Prometheus alone, and typically requires capacity planning around ingestion rate, label cardinality, and object storage throughput.
Common alternatives include Thanos, Cortex, VictoriaMetrics, and InfluxDB, each with different trade-offs in deployment model, query behavior, and cost. Upstream documentation is available at https://grafana.com/oss/mimir/.
Our experience with Grafana Mimir helped us develop practical reference architectures, runbooks, and automation for teams that need to store and query Prometheus metrics reliably at scale, especially when moving from single-cluster monitoring to multi-environment, multi-tenant observability.
Some of the things we did include:
- Designed and implemented production-grade Grafana Mimir deployments on Kubernetes with clear separation of read/write paths, right-sized resources, and predictable scaling behavior.
- Assessed and improved Prometheus remote_write pipelines, including batching/queue tuning, failure modes, and safe cutover plans from existing Prometheus setups.
- Implemented multi-tenant governance with consistent label conventions, per-tenant limits, and guardrails to control cardinality and prevent noisy or runaway workloads.
- Integrated Mimir with Grafana for tenant-aware dashboards, standardized folder structures, and permission models aligned to platform and product teams.
- Built alerting and rules workflows using Prometheus and Mimir rule evaluation, including sizing guidance, recording rules, and operational policies for change control.
- Hardened object storage backends (S3-compatible and cloud-native) with lifecycle policies, encryption, and retention strategies optimized for long-term metric storage and predictable cost.
- Established high availability and disaster recovery approaches, including zone-aware deployments, replication considerations, and tested restore procedures for common incident scenarios.
- Optimized query performance by tuning compaction, caching, and query-frontend behavior, and by identifying high-cost queries and label patterns that degraded latency.
- Automated deployments and upgrades with GitOps-style workflows, including configuration validation, safe rollouts, and repeatable promotion across environments.
- Improved “observability of the observability stack” by instrumenting Mimir itself, building SLO-oriented dashboards, and documenting on-call playbooks for incident response.
This experience helped us accumulate significant knowledge across multi-tenant, multi-cluster, and high-retention monitoring use cases, enabling us to deliver high-quality Grafana Mimir setups that are maintainable, cost-aware, and aligned with how teams actually operate.
Some of the things we can help you do with Grafana Mimir include:
- Assess your Prometheus remote_write pipeline and deliver a findings report covering scalability, retention, reliability, and operational risk.
- Define an adoption roadmap for multi-tenant metrics storage aligned to SLOs, growth forecasts, and governance requirements.
- Design and implement a production-ready Grafana Mimir architecture (single or multi-cluster) with clear failure domains, HA, and disaster recovery.
- Deploy and operate Mimir on Kubernetes using Infrastructure as Code and GitOps workflows for repeatable, auditable environments.
- Implement tenant isolation and security guardrails (authn/authz, encryption, quotas, and least-privilege access) to support compliance-ready operations.
- Optimize cost and performance with retention policies, ingestion and compaction tuning, query optimization, and capacity planning for predictable spend.
- Troubleshoot ingestion errors, high cardinality, query latency, and compactor/store-gateway bottlenecks to stabilize dashboards and alerting.
- Establish day-2 operations with monitoring, alerting, runbooks, autoscaling strategies, backup/restore, and safe upgrade playbooks.
- Enable your team with hands-on workshops and operational documentation so ownership stays in-house after delivery.
For product details and architecture guidance, see Grafana Mimir.
