O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.

Observability in the world of microservices

88 visualizações

Publicada em

This talk contains observability in microservices. It has Prometheus, Fluentd, Open Tracing, Jaeger.

Publicada em: Engenharia
  • Seja o primeiro a comentar

Observability in the world of microservices

  1. 1. Observability in the world of Microservices Chandresh Pancholi
  2. 2. About me ● Working as Software engineer and leading India office for One Concern ● Worked with Flipkart & Arvind group ● Apache committer for project Apache gossip ● Speaker at Meetups & Conferences Coordinates: Email: chandresh@oneconcern.com Linkedin: https://www.linkedin.com/in/chandresh-pancholi-467a8015/
  3. 3. About One Concern One concern is a multi-hazard platform which is on the mission of saving lives and build resilience & livelihood everywhere. Our platform provides unprecedented situational awareness and actionable insights for decision-makers. One Concern currently monitors 12,076,661 residential and 651,917 commercial buildings. We monitor earthquakes for 36M people. website: https://oneconcern.com
  4. 4. Monolith vs Microservice
  5. 5. Observability “Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs”.
  6. 6. Pillars of Observability 1. Monitoring 2. Logging 3. Tracing
  7. 7. Monitoring 1. Prometheus 2. Graphite 3. InfluxDB
  8. 8. Logging 1. FluentD 2. FluentBit 3. Logstash
  9. 9. Tracing ● Jaeger ● Zipkin ● Kiali
  10. 10. Jaeger Architecture
  11. 11. Jaeger benefits ● Distributed transaction monitoring ● Performance & latency optimisation ● Root cause analysis ● Service dependency analysis ● Distributed context propagation
  12. 12. Jaeger features ● Uses consistent upfront sampling with individual per service/endpoint probabilities ● Multiple storage backends: Cassandra, Elasticsearch, memory. ● Adaptive sampling ● Post-collection data processing pipeline ● Libraries available in Java, GO, Node, Python, C++
  13. 13. Terminology ● Span ⇒ A span represents a logical unit of work in Jaeger that has an operation name, the start time of the operation, and the duration. Spans may be nested and ordered to model causal relationships. ● Trace ⇒ A trace is a data/execution path through the system, and can be thought of as a directed acyclic graph of spans.
  14. 14. Demo
  15. 15. We Are Hiring?

×