Infrastructure Audit

Modern information systems consist of many interconnected subsystems. Each of them operates according to its own software methodology and, as a rule, is built on a separate software stack. Let DevOpsProdigy's team of experts assess your stack and help you fine tune it. Contact us today to get intouch with one of our IT experts.

The audit is conducted in two stages:

I. Audit of monitoring and critical problems

  • Operational analysis of the current architecture to identify and address critical problems and, if necessary, make changes to the architecture
  • Audit of monitoring systems in the existing infrastructure
  • Improvement of monitoring systems based on identified infrastructure features
  • Audit of the failure alert system
  • Improvement and adjustment of the failure alert system based on identified infrastructure features
  • Audit of the organization of duty shifts, proposals for improvement based on our own company’s experience
  • Audit of escalation plan within the technical support department
  • Documentation based on the audit results

II. Audit of infrastructure

  • Analysis of infrastructure stability
  • Audit of the reliability of backup systems, suggestions for improvement
  • Analysis of the operation of project backup systems, proposals for improving backup systems, organization of a plan for regular switching to the backup site
  • Analysis of DBMS operation, suggestions for improvement
  • Consultations on working with technologies from the Apache Foundation and their applicability in the company's infrastructure
  • Documentation with recommendations for applying the proposed changes in the operation of the company's infrastructure

Technology stack:

The technologies we apply in DevOpsProdigy include but not limited to the following:

  • Monitoring and visualization systems - Prometheus, Grafana, TICK Stack, Zabbix, Nagios, Icinga, DataDog, NewRelic,
  • Incident response systems - PagerDuty, Amixr
  • Logging, error tracking - ELK, EFK, Grafana Loki, Graylog, Sentry
  • Tracing systems - Jaeger, Zipkin
  • Web, ingress and application servers - Nginx, Envoy, Linkerd, Traefik, Apache, HAProxy, Jetty, Tomcat, NodeJS
  • Programming languages - Python, TypeScript, JavaScript, Go, Java, PHP, Ruby, Erlang
  • Cloud computing platforms and services - Amazon AWS, Google Cloud Platform, Microsoft Azure, Rackspace, Alibaba Cloud
  • Container systems: Docker, CRI-O, LXC, LXD
  • Container Orchestration: Kubernetes, Nomad, Docker Swarm, RedHat OpenShift, Mesos/Marathon
  • Automation tools: Jenkins, Gitlab CI, CircleCI, Travis CI, Bitbucket Pipelines, TeamCity, GoCD, ArgoCD, Spinnaker
  • Cloud automation tools: AWS CodePipeline, AWS CodeDeploy, AWS CodeCommit, Google CloudBuild, Spinnaker
  • Cloud databases: AWS RDS and other DBs, Google Cloud SQL and other DBs, Firebase, MongoDB Atlas
  • IaaC: Terraform, Pulumi, Ansible, Chef, Puppet
  • Service Mesh: Istio, Maesh, Linkerd
  • Service Discovery: Consul, etcd, ZooKeeper, MongoDB
  • On-Premise Databases: PostgreSQL, MongoDB, MySQL, Cassandra, Elastic, Redis, MemSQL, Galera, Aerospike, MSSQL, Clickhouse, InfluxDB
  • Messaging systems: Apache Kafka, RabbitMQ, Apache Beam, Mosquitto
  • Storages for Big Data Applications: Apache Hadoop, Apache HBase, Greenplum, Cassandra
  • Query Engines: Apache Hive, Apache Impala
  • Data processing and transformation: Apache Spark, Apache Flink, Apache Airflow, Apache NiFi, Kafka Streams

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