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A Journey of Auditlogs from
Kafka to Open Search (Elastic
Search)
Muhammad Arslan
Big Data/AI Architect
Agenda
• Overview
• Service Architecture
• Kafka
• Open Search (Elastic Search)
• Monitoring and Alerting
• Security
• Data Backup
• Disaster Recovery
• Questions?
Overview
• What is auditlog?
• What is changed and who changed it.
• Previous state vs Current state
• Auditlogs are essentials part of critical applications
• Gets tricky when having multiple microservices
• Centralized solution that supports all kind of logs
• Don’t lose any logs, as they are critical
• 2 phase commit to track when and what has
happened
Requirements
• SLOs (99% < 100ms, 75% < 30ms)
• Can scale easily
• No Downtime (Thanks to green and blue
deployments)
• Terraform the whole infrastructure
• No vendor cloud lock-in
• Alerts and monitoring
Prestudy POC
Full cloud-native Managed services +
custom loader
SNS + SQS Direct writes to ES Kafka + ES
Managed Services:
• Kinesis
• Kinesis Data
Firehose
• ElasticSearch
Custom services:
• Rest API to validate
and push to Kinesis
• Rest API for search
Managed services:
• Kinesis
• ElasticSearch
Custom services:
• Rest API to
validate and push
to Kinesis
• Rest API for search
• Kinesis consumer
that writes to ES
Managed services:
• SNS
• SQS
ElasticSearch
• Custom services:
• Rest API to validate
and push to SNS
• Rest API for search
• Custom sqs
consumer/writer
for each
destination
Managed services:
• ElasticSearch
Custom services
• Rest API to validate
and push to
Elasticsearch and
others
Managed services:
• ElasticSearch
• Kafka
Custom services
• Rest API to validate
and push to Kafka
• Rest API for search
• Custom Kafka
consumer/writer
for each
destination
Service Architecture
Write API
• Endpoint for posting auditlog
• 2 phase commit
• entryId => UUID
• Transaction State:
• STARTED
• COMPLETED
• FAILED
• UNKNOWN
• Same entryId for the following request
• Hash(entryId1 + STARTED)
• Hash(entryId1 + [COMPLETED | FAILED | UNKNOWN])
Sample
Request
Kafka
• Write Rest API receives the event and put it in Kafka topic
• Retention 5 days
• 10 partitions for topic (as a start)
• The message is compressed in avro format
Kafka to
ElasticSearch
(OpenSearch)
connector
Reads events from Kafka topic
Based on the event date, ingest
it into monthly index
Example:
Index-prefix + 2022-08-01
Index-prefix + 2022-09-01
Kafka to S3 connector (Backup)
• Connector that copies all the s3 bucket as backup
• Files are stored hourly basis in avro format
• Can be used to reprocess or replay the data
• Retention time 3 months
• Deleted automatically after 3 months
OpenSearch (ElasticSearch)
• Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) is a
managed service that makes it easy to deploy, operate, and scale OpenSearch
clusters in the AWS Cloud.
• Amazon OpenSearch Service supports OpenSearch and legacy Elasticsearch
OSS.
• OpenSearch is a fully open-source search and analytics engine for use cases
such as log analytics, real-time application monitoring, and clickstream
analysis.
• You can scale your cluster with a single API call or a few clicks in the console.
AWS OpenSearch
Setup (Int and
Prod)
OpenSearch Index
15
OpenSearch
ILM
Index
template
• An index template is a way to tell
Elasticsearch how to configure an index
when it is created.
• Templates are configured prior to index
creation.
• When an index is created - either manually
or through indexing a document - the
template settings are used as a basis for
creating the index.
• GET _index_template/auditlog-template
17
Index
Template
Policy
template
• To use a policy to manage an index that
doesn’t roll over.
• you can specify a lifecycle policy when you
create the index, or apply a policy directly to
an existing index.
• To maintain the state of the index
• Hot
• Warm (Ultrawarm)
• Cold
• Delete
19
Policy
Template
Ingestion pipeline
Calculate storage
requirements
• Source Data * (1 + Number of Replicas) * 1.45 =
Minimum Storage Requirement
• 30 * (1 + 2) * 1.45 = 130,5
22
Data backup and recovery
• Automatic snapshots 1 week retention
• Manual snapshots can be done and transferred to s3
bucket automatically
• Data can be restored any time from automatic or manual
snapshots
Monitoring
• Auditlog Platform
• Auditlog OpenSearch
• Dataflow-connect
• Dataflow-msk
• Dataflow-producer
Auditlog Platform Monitoring
OpenSearch Monitoring
MSK Monitoring
Security
• OpenSearch UI is behind Oauth proxy
• No IAM or SSO based security
• Currently can’t track any user who performed any queries
other then logs
Data Backup
• Automatic
snapshots
• Manual
snapshots
Create
restore
snapshots
runbook
Replay to get
to handle
data
inconsistency
S3 Replay
docs
Disaster Recovery : Exercise
• Exercise in integration environment
• Update domain i.e add more data nodes lower down instance size
• Stop replicas es connector and monitoring
• Drop all daily indices
• Apply ingestion monthly policy
• Apply new datamodel pointing to ingestion monthly policy
• Start replicas of es connector and monitoring
Questions

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[DSC Europe 23] Muhammad Arslan - A Journey of Auditlogs from Kafka to Elastic Search

  • 1. A Journey of Auditlogs from Kafka to Open Search (Elastic Search) Muhammad Arslan Big Data/AI Architect
  • 2. Agenda • Overview • Service Architecture • Kafka • Open Search (Elastic Search) • Monitoring and Alerting • Security • Data Backup • Disaster Recovery • Questions?
  • 3.
  • 4. Overview • What is auditlog? • What is changed and who changed it. • Previous state vs Current state • Auditlogs are essentials part of critical applications • Gets tricky when having multiple microservices • Centralized solution that supports all kind of logs • Don’t lose any logs, as they are critical • 2 phase commit to track when and what has happened
  • 5. Requirements • SLOs (99% < 100ms, 75% < 30ms) • Can scale easily • No Downtime (Thanks to green and blue deployments) • Terraform the whole infrastructure • No vendor cloud lock-in • Alerts and monitoring
  • 6. Prestudy POC Full cloud-native Managed services + custom loader SNS + SQS Direct writes to ES Kafka + ES Managed Services: • Kinesis • Kinesis Data Firehose • ElasticSearch Custom services: • Rest API to validate and push to Kinesis • Rest API for search Managed services: • Kinesis • ElasticSearch Custom services: • Rest API to validate and push to Kinesis • Rest API for search • Kinesis consumer that writes to ES Managed services: • SNS • SQS ElasticSearch • Custom services: • Rest API to validate and push to SNS • Rest API for search • Custom sqs consumer/writer for each destination Managed services: • ElasticSearch Custom services • Rest API to validate and push to Elasticsearch and others Managed services: • ElasticSearch • Kafka Custom services • Rest API to validate and push to Kafka • Rest API for search • Custom Kafka consumer/writer for each destination
  • 8. Write API • Endpoint for posting auditlog • 2 phase commit • entryId => UUID • Transaction State: • STARTED • COMPLETED • FAILED • UNKNOWN • Same entryId for the following request • Hash(entryId1 + STARTED) • Hash(entryId1 + [COMPLETED | FAILED | UNKNOWN])
  • 10. Kafka • Write Rest API receives the event and put it in Kafka topic • Retention 5 days • 10 partitions for topic (as a start) • The message is compressed in avro format
  • 11. Kafka to ElasticSearch (OpenSearch) connector Reads events from Kafka topic Based on the event date, ingest it into monthly index Example: Index-prefix + 2022-08-01 Index-prefix + 2022-09-01
  • 12. Kafka to S3 connector (Backup) • Connector that copies all the s3 bucket as backup • Files are stored hourly basis in avro format • Can be used to reprocess or replay the data • Retention time 3 months • Deleted automatically after 3 months
  • 13. OpenSearch (ElasticSearch) • Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) is a managed service that makes it easy to deploy, operate, and scale OpenSearch clusters in the AWS Cloud. • Amazon OpenSearch Service supports OpenSearch and legacy Elasticsearch OSS. • OpenSearch is a fully open-source search and analytics engine for use cases such as log analytics, real-time application monitoring, and clickstream analysis. • You can scale your cluster with a single API call or a few clicks in the console.
  • 17. Index template • An index template is a way to tell Elasticsearch how to configure an index when it is created. • Templates are configured prior to index creation. • When an index is created - either manually or through indexing a document - the template settings are used as a basis for creating the index. • GET _index_template/auditlog-template 17
  • 19. Policy template • To use a policy to manage an index that doesn’t roll over. • you can specify a lifecycle policy when you create the index, or apply a policy directly to an existing index. • To maintain the state of the index • Hot • Warm (Ultrawarm) • Cold • Delete 19
  • 22. Calculate storage requirements • Source Data * (1 + Number of Replicas) * 1.45 = Minimum Storage Requirement • 30 * (1 + 2) * 1.45 = 130,5 22
  • 23. Data backup and recovery • Automatic snapshots 1 week retention • Manual snapshots can be done and transferred to s3 bucket automatically • Data can be restored any time from automatic or manual snapshots
  • 24.
  • 25. Monitoring • Auditlog Platform • Auditlog OpenSearch • Dataflow-connect • Dataflow-msk • Dataflow-producer
  • 29. Security • OpenSearch UI is behind Oauth proxy • No IAM or SSO based security • Currently can’t track any user who performed any queries other then logs
  • 30.
  • 31. Data Backup • Automatic snapshots • Manual snapshots Create restore snapshots runbook Replay to get to handle data inconsistency S3 Replay docs
  • 32. Disaster Recovery : Exercise • Exercise in integration environment • Update domain i.e add more data nodes lower down instance size • Stop replicas es connector and monitoring • Drop all daily indices • Apply ingestion monthly policy • Apply new datamodel pointing to ingestion monthly policy • Start replicas of es connector and monitoring