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WeAreDevelopers LIVE β€’ Feb 12, 2024

Serverless Observability: where SLOs meet transforms

Diana Todea

Transitioning to serverless often breaks traditional monitoring. Stop relying on outdated aggregations. Learn how Elasticsearch Transforms power dynamic SLOs to protect your error budgets proactively.

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#1 about 3 min

Migrating to serverless observability and data transforms

How large dataset environments scale data manipulation by converting Elasticsearch indices into summarized indices.

#2 about 4 min

Defining service level indicators, objectives, and agreements

Core equations and characteristics that separate actionable service level objectives from poorly defined metrics.

#3 about 4 min

Types of service level indicators in Elasticsearch

How to select and configure different indicator types for tracking logs, latency, and transactions.

#4 about 3 min

Transform architecture and summarizing index data

The mechanics of persistent tasks that convert source indices into summarized datasets for optimized queries.

#5 about 4 min

Creating data transforms and health alerts visually

Steps to configure persistent transform rules and set up health alerting via the stack management interface.

#6 about 3 min

Configuring burn rate alerts for error budgets

Calculating the rate of error budget consumption over multiple time windows to prevent alert fatigue.

#7 about 4 min

Defining service level objectives and dashboards in Kibana

A practical walkthrough of creating a service level objective and visualizing it on an aggregated dashboard.

#8 about 3 min

Managing transforms and objectives via developer tools APIs

Utilizing Elasticsearch APIs for deploying, configuring, and troubleshooting transforms during incidents.

#9 about 9 min

Integrating service level objectives into incident management

How site reliability engineers coordinate with product teams and customer support to align user expectations.

#10 about 3 min

Managing objective variants across serverless environments

Strategies for iterating and adjusting basic cluster indicators based on continuous system feedback.

#11 about 3 min

Setting realistic measurement targets and monitoring tools

Why organizations should avoid overly ambitious percentiles at launch and build custom observation tools.

#12 about 4 min

Tracking improvement impacts and cold start indicators

Correlating internal monitoring feedback with external agreements to validate objective performance against new deployments.

#13 about 5 min

Aligning cross-team goals and prioritizing backlog improvements

Fostering communication across engineering departments to prioritize reliability issues ahead of scheduled system upgrades.

#14 about 5 min

Incorporating user feedback and third-party dependency data

Synchronizing feature prioritization with objective stability and managing expectations for external tooling.

#15 about 4 min

Balancing feature releases with reliable service targets

Distributing responsibilities between software developers and site reliability teams while keeping runbook documentation updated.

#16 about 4 min

Evaluating transform scalability and small product adoption

Measuring the complexity and architectural impact before integrating data transforms within modest infrastructure setups.

Matching moments

6:29 min

Answering inquiries on SLA negotiations and observability tooling

Martin BerΓ‘nek Β· LIVE

1:04 min

Embedding deep observability into serverless operations seamlessly

Modood Alvi Β· WWC 2025

5:05 min

Exploring hybrid models, monoliths, and serverless computing

Michael Eisenbart Β· LIVE

3:22 min

Real-world challenges in adopting serverless architectures

Nočnica Fee · LIVE

12:33 min

Exploring advanced observability stacks and distributed infrastructure challenges

Pawel Piwosz Β· LIVE

17:03 min

Introduction to metrics and observability challenges in monitoring

Liam Hurrell Β· LIVE

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