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The rapid software development process that exists today requires an expanding and complex infrastructure and application components, and the job of operations and development teams is ever growing and multifaceted. Observability, which helps manage and analyze telemetry data, is the key to ensuring the performance and reliability of your applications and infrastructure. In particular, logs are the main default signal developers enable, providing a significant amount of detail for debugging, performance analysis, security, and compliance management. So how do you define a strategy to get the most out of your logs?
In this blog post, we’ll explore:
- The logging journey, which reviews the collection, processing and enrichment, and analysis and rationalization of logs
- The difference between managing structured and unstructured data from logs
- Whether traces should replace logs
- Improving operational efficiency for logs, by understanding how to reduce time in transformation, centralized versus decentralized log storage, and how and when to reduce what is stored
By gaining a deeper understanding of these topics, you’ll be better equipped to manage logs effectively and ensure the reliability, performance, and security of your applications and infrastructure.
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Let’s cover how logs should be collected and ingested, what is proper parsing and processing, and how you can analyze and rationalize the logs. Additionally we will also discuss how to enhance this journey with application performance monitoring (APM), metrics, and security events.
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In addition to helping with RCA, finding unknown-unknowns and improving troubleshooting organizations should look for forecasting functionality to help them project future demand and calibrate business goals.
src:10.42.42.42
client_ip:10.42.42.42
apache2.access.remote_ip: 10.42.42.42
context.user.ip:10.42.42.42
src_ip:10.42.42.42,
Having an IP address represented in multiple ways introduces complexities in analyzing potential problems or even identifying them.
With a common schema, all the incoming data is in a standardized format. Taking the above example, each of the sources would identify the client’s IP address the same way.
source.ip:10.42.42.42,
This helps reduce the need to spend time transforming data.
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