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Testimonials
They have been great at adjusting and improving as we have worked together.
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.
I was impressed with the amount of professionalism, communication, and speed of delivery.
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.
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.
They are very knowledgeable in their area of expertise.
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.
Nguyen is a champ. He's fast and has great communication. Well done!
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.
You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
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?
VictoriaMetrics is a high-performance time-series database and monitoring backend used to ingest, store, and query metrics efficiently at scale. It is commonly used by DevOps and SRE teams running Prometheus-style monitoring who need longer retention, reliable ingestion, and responsive dashboards and alerting without excessive infrastructure overhead.
It typically runs on Linux or Kubernetes and integrates into existing observability pipelines as a remote storage and query layer via Prometheus-compatible remote_write/remote_read. For related platform work, see DevOps consulting.
- Efficient ingestion and compression for large volumes of time-series metrics
- Fast query performance for dashboards and alert rule evaluations
- Prometheus compatibility, including familiar query patterns and tooling
- Configurable retention policies for short- and long-term metrics storage
- Deployment options from single-node setups to clustered architectures for higher availability
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.
VictoriaMetrics is a high-performance time-series database and monitoring backend used to store and query Prometheus-style metrics efficiently at scale. It is often chosen when Prometheus local storage becomes too expensive, retention requirements grow, or query performance degrades under high ingestion volume.
- High ingestion throughput supports large Kubernetes fleets and high-cardinality metrics with fewer write bottlenecks.
- Efficient compression reduces disk usage, improving cost for long retention windows and large metric volumes.
- Fast query execution keeps dashboards and alert evaluations responsive, including wide time-range queries and heavy aggregations.
- Prometheus ecosystem compatibility fits common scrape, remote_write, and exporter patterns to reduce migration friction.
- Remote write offload lets Prometheus focus on scraping and short-term alerting while VictoriaMetrics provides durable, long-term storage.
- Flexible deployment options support single-node setups for smaller environments and clustered components for horizontal scale and higher availability.
- Multi-tenancy features enable shared observability platforms with isolation across teams, environments, or customers.
- Operational simplicity can be lower than multi-component long-term storage stacks, which helps reduce day-2 maintenance overhead.
- Retention controls and optional downsampling patterns help manage data growth while keeping common queries performant.
VictoriaMetrics is a strong fit for centralizing metrics across many clusters, extending retention from weeks to months or years, and improving query latency under sustained load. Key trade-offs typically include validating PromQL compatibility for critical queries and alerts, and selecting a cluster topology that matches availability, write throughput, and failure-domain requirements.
Common alternatives include Prometheus, Thanos, Cortex, and InfluxDB. Reference documentation: https://victoriametrics.com/.
Our experience with VictoriaMetrics helped us build practical runbooks, automation patterns, and capacity models that we reuse to deliver scalable, cost-efficient metrics storage and consistently fast querying for client observability platforms.
Some of the things we did include:
- Designed VictoriaMetrics architectures (single-node and cluster) with clear retention, downsampling, and sizing assumptions aligned to alerting and dashboard SLOs.
- Implemented Kubernetes deployments with hardened manifests, sane resource requests/limits, anti-affinity, disruption-safe rollouts, and predictable storage provisioning.
- Migrated workloads from Prometheus to VictoriaMetrics using staged
remote_writecutovers, query validation, and dashboard parity checks to reduce risk. - Integrated VictoriaMetrics with Grafana for consistent dashboards, datasource tuning, and query performance improvements for high-cardinality environments.
- Built HA and failure-domain-aware cluster layouts (vmstorage/vminsert/vmselect) with replication, sharding strategies, and operational guardrails to reduce blast radius.
- Optimized ingestion and query performance through label hygiene, relabeling rules, scrape interval reviews, and cardinality controls to prevent index and cost runaway.
- Established observability for the metrics platform itself (health, saturation, ingestion lag, and query latency) with actionable alerts and on-call playbooks.
- Implemented backup/restore and disaster recovery procedures, including periodic restore drills and documented RPO/RTO targets for regulated or high-availability workloads.
- Automated configuration and release workflows using GitOps-style change management, environment promotion, and smoke tests for critical queries and alerts.
- Delivered operator training and handover for SRE/DevOps teams, covering troubleshooting patterns like remote_write backpressure, noisy labels, and storage growth anomalies.
This experience helped us accumulate significant knowledge across multiple VictoriaMetrics use-cases, from Kubernetes-first deployments to large-scale migrations and performance tuning, enabling us to deliver reliable VictoriaMetrics setups that are easier to operate, scale, and cost-control over time.
Some of the things we can help you do with VictoriaMetrics include:
- Assess your current metrics pipeline and monitoring backend, delivering a written report with risks, bottlenecks, and prioritized recommendations.
- Create an adoption roadmap for VictoriaMetrics covering retention, downsampling, cardinality controls, and SLO-driven observability practices.
- Design and implement production-ready VictoriaMetrics architectures (single-node or cluster) with capacity planning, HA considerations, and failure-mode reviews.
- Deploy and operate VictoriaMetrics on Kubernetes using GitOps, repeatable infrastructure-as-code, and day-2 operational runbooks.
- Migrate from Prometheus to VictoriaMetrics with minimal disruption, including remote_write/remote_read setup, query compatibility checks, and staged rollout plans.
- Optimize cost and performance through storage sizing, retention tuning, query optimization, and dashboard/alert responsiveness improvements.
- Implement security guardrails such as TLS, authentication/authorization patterns, network segmentation, and least-privilege access to metrics data.
- Improve reliability with backup/restore procedures, disaster recovery planning, ingestion/query health alerting, and operational dashboards.
- Troubleshoot ingestion and query issues (high cardinality, backpressure, slow queries) and deliver actionable remediation steps.
- Enable your team with hands-on training, documentation, and operational playbooks for consistent day-2 operations and continuous improvement.
