Event Streaming with Apache Kafka Corporate Training
Build event streaming skills your team can use immediately
This instructor-led program helps your team design, operate, and scale Apache Kafka pipelines for real-time analytics, with guided hands-on labs in every module.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build a real-time analytics team
The Edstellar EVENT STREAMING WITH APACHE KAFKA Capability Model
Diagnose
Map how events flow through your systems today and where latency or gaps hurt decisions.
Standardize
Align on topic design, schema rules, and naming conventions across producers and teams.
Practice
Build producers, stream processors, and connectors in guided hands-on labs on real clusters.
Measure
Track lag, throughput, and data freshness with dashboards tied to business outcomes.
Scale
Roll out reusable streaming patterns across products with tested templates and runbooks.
Need more than one program?Get a group quote
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Program Overview: What is Event Streaming with Apache Kafka?
Event Streaming with Apache Kafka is a 28-hour, hands-on program for data engineers, platform teams, and backend developers who need to move from batch jobs to real-time data. It covers Kafka architecture, producers and consumers, message reliability, cluster operations, Kafka Streams, and Kafka Connect with Schema Registry. Participants learn by building pipelines that carry real events, not by watching slides about them.
Training is lab-driven from the first session. Participants stand up multi-broker Kafka clusters, tune producers and consumers for exactly-once semantics, and break clusters on purpose to practice recovery. Instructors with production streaming experience review every topology, schema design, and failure drill, giving feedback on the choices teams would actually face on call. Guided exercises build from simple topics to stream joins and windowed aggregations, and the program closes with a capstone where each team ships a production-grade streaming analytics platform.
Most teams start streaming with ad-hoc scripts and hope: topics multiply, schemas drift, and nobody knows what happens when a broker dies. This program replaces that guesswork with disciplined practice, teaching teams to design for failure, govern schemas, and monitor lag before customers feel it. The result is streaming infrastructure the business can trust.
The capstone is the proof: a production streaming analytics platform each team designs, builds, and defends, with producers, consumers, Connect pipelines, and stream processing running against realistic data volumes. Reviewers probe the failure modes, the schema evolution story, and the recovery plan, the way an incident review would. Teams walk out with an architecture they can justify in a design review and the operational muscle memory to run it at 3 a.m.
Edstellar delivers this program as instructor-led training in hybrid, onsite, or live virtual formats, shaped around your team's stack and use cases. Content adapts to your tooling and data volumes, so every lab mirrors the streaming work your engineers and analysts actually own. Your team learns to choose delivery semantics, monitor lag and throughput, evolve schemas safely, and connect Kafka to the dashboards and models your business relies on. By the end, participants can ship streaming pipelines that feed decisions in real time.
What's Included in this Workshop for Your Enterprise Teams
- 1
Streaming foundations
Kafka architecture, producers, consumers, and reliability.
- 2
Cluster operations
Replication, monitoring, rebalancing, and security.
- 3
Stream processing
Kafka Streams apps with windowing and joins.
- 4
Data movement
Connectors, schema evolution, and ingestion validation.
- 5
Analytics and capstone
Live dashboards and a production platform build.
- Instructor-led sessions with a Kafka practitioner
- Hybrid, onsite, or live virtual delivery
- Guided hands-on labs in every module
- Lab environments and workbooks included
- Skills assessment and completion summary
- Post-training support for your team
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
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- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Event Streaming with Apache Kafka Course Topics and Program Outline
Seven modules take your team from Kafka fundamentals to a production streaming analytics platform.
Built by Edstellar with streaming platform expertise
Built by practitioners who run Kafka clusters in production, shaped around your stack and use cases.
We review your team's Kafka maturity, data volumes, and analytics goals to shape every lab.
Instructor-led sessions cover streaming models, Kafka architecture, and reliability patterns with live demos.
Guided hands-on labs on working clusters: producers, stream processing, connectors, and live dashboards.
Your team ships a capstone streaming platform that feeds decisions with real-time analytics.
Your team leaves with a working Kafka streaming platform and the skills to run it in production.
Delivered as
Delivered as instructor-led training in hybrid, onsite, or live virtual formats, scheduled around your team's working hours.
Start a local Kafka cluster and publish and consume your first messages.
learna)Streaming versus batch processing models
b)Kafka cluster architecture: brokers, topics, and partitions
c)Producer and consumer roles in the ecosystem
d)Real-time analytics use cases across industries
Build a producer and consumer pair and tune delivery semantics for a retry-safe workflow.
learna)Producer tuning: acknowledgments, batching, and compression
b)Consumer groups, offset commits, and rebalancing
c)Serialization formats and schema design basics
d)Delivery semantics: at-least-once versus exactly-once
Rebalance partitions across brokers and recover a simulated broker failure with minimal lag.
practicea)Replication, in-sync replicas, and leader election
b)Partition assignment and rebalancing strategies
c)Monitoring lag, throughput, and broker health
d)Securing clusters with SASL authentication and SSL
Build a streaming aggregation application with windowed counts over live order events.
practicea)KStreams and KTables programming model
b)Windowing and real-time aggregations
c)Stream-stream and stream-table joins
d)State stores and processing guarantees
Wire a database source connector to Kafka and enforce schema compatibility on every record.
practicea)Source and sink connectors for databases and files
b)Schema evolution and compatibility rules
c)Data validation pipelines at ingestion time
d)Building and testing connector workflows
Build an end-to-end pipeline that streams events into a live dashboard with alerts.
applya)Streaming queries with SQL-style engines
b)Connecting Kafka to analytics dashboards
c)Data modeling patterns for streaming data
d)Alerting and storytelling with live metrics
Deliver a working streaming platform with dashboards, monitoring, and a solution walkthrough.
applya)Designing a full streaming analytics platform
b)Building, securing, and monitoring the pipeline
c)Documenting and presenting your solution
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Practical streaming skills your engineers and analysts apply to production Kafka pipelines.
Design Kafka topics and partitions
Structure topics, keys, and partitions so streams scale with your data volumes.
Tune producers and consumers
Configure throughput, durability, and delivery semantics for each workload.
Operate resilient clusters
Monitor lag and broker health, rebalance partitions, and recover from failures.
Build stream-processing apps
Write Kafka Streams jobs with windowing, joins, and stateful aggregations.
Move data with connectors
Ingest and sink data with Kafka Connect while evolving schemas safely.
Query and visualize live streams
Turn streaming data into dashboards, alerts, and stories that drive decisions.
Ship production streaming platforms
Design, secure, and document end-to-end analytics platforms on Kafka.
Teams that Benefit from this Event Streaming with Apache Kafka Group Training
Built for engineers, analysts, and architects who own streaming data. Content adapts to each role and experience level, so every cohort practices the workflows it owns.
Streaming pipelines your teams can trust
Give pipeline owners the skills to design topics, tune throughput, and operate Kafka clusters that stay healthy.
Workflow friction
- Consumer lag under load
- Schema changes breaking pipelines
- Manual cluster firefighting
How the program helps
- Reliable topic and partition design
- Faster streaming pipeline delivery
- Fewer production incidents
Practice use cases
- topic design
- producer tuning
- cluster operations
Real-time insight from live data
Help analysts and BI teams query streams directly and build dashboards that update as events arrive.
Workflow friction
- Stale batch-only reporting
- Fragile data extracts
- Slow ad-hoc queries
How the program helps
- Live dashboards and alerts
- Faster insight delivery
- Trustworthy streaming metrics
Practice use cases
- streaming queries
- live dashboards
- insight storytelling
Kafka platforms that scale safely
Equip platform engineers with monitoring, security, and capacity practices for shared Kafka infrastructure.
Workflow friction
- Unsecured cluster access
- Noisy-neighbor workloads
- Unclear ownership of topics
How the program helps
- Standardized cluster operations
- Secure multi-team access
- Predictable capacity planning
Practice use cases
- monitoring setup
- access control
- capacity planning
Event-driven services done right
Teach application teams to publish and consume events with the right delivery semantics and error handling.
Workflow friction
- Tightly coupled services
- Lost or duplicated events
- Inconsistent event formats
How the program helps
- Cleaner event contracts
- Resilient event consumers
- Safer deploys of producers
Practice use cases
- event contracts
- consumer design
- error handling
Cohorts can mix roles or focus on one function; labs adapt to your team's tools and data.
Prerequisites: This program benefits data engineers, analysts, and developers who work with data pipelines. Basic programming experience and familiarity with databases or messaging concepts help, but neither is required. No prior Kafka experience is needed. Content adapts to each cohort's tools, data volumes, and streaming use cases.
Data Engineer to Streaming Platform Lead
A role-based path from Kafka fundamentals to leading streaming platforms across the data estate.
A learning path that grows with data careers, from Kafka basics to confident streaming platform ownership.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your teams and schedules. Every mode is instructor-led with guided hands-on labs.
Hybrid Training
Blend onsite and live virtual sessions so distributed teams learn together with one instructor and shared labs.
- Mixed onsite and virtual cohorts
- Shared cloud lab environments
- One instructor across sessions
- Flexible scheduling by module
Onsite Training
We deliver the program at your office with lab environments ready, so your team practices together in one room.
- Training at your location
- Team builds together in person
- Labs on your network stack
- Whiteboard design sessions
Live Virtual Training
Join live instructor-led sessions online with the same guided labs, breakout builds, and instructor feedback.
- Live instructor interaction
- Cloud-based lab environments
- Breakout practice sessions
- Recordings and workbooks
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, preferred dates, and delivery mode, and we will send a tailored quote within one business day.
Yes. A short discovery call helps us map your streaming goals and shape the labs to your stack before you commit.
Yes. Live virtual sessions are instructor-led with the same guided labs, breakout practice, and direct feedback.
Yes. We deliver onsite worldwide, with lab environments prepared so your team starts building on day one.
The program runs 28 instructor-led hours, typically over four to five days, with a capstone platform build.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Kafka streaming builds on basic pipeline skills, so they come first. After your team can stream with Kafka, Beam adds unified batch and stream processing, and the path ends with designing a streaming architecture.
Why Choose Edstellar as Your Event Streaming with Apache Kafka Training Provider
Edstellar delivers Kafka training built around your stack, your data, and your team's streaming goals.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Content adapts to your Kafka setup, data volumes, and use cases, so every lab mirrors the streaming work your team owns.
Proven Methodology
A learn, practice, apply arc moves your team from streaming concepts to a working platform with measurable progress.
Practice-Based Learning
Guided hands-on labs on working clusters in every module build muscle memory for producers, streams, and connectors.
Expert Trainers
Instructors are practitioners who operate Kafka in production and coach teams through real pipeline builds.
Global Scale
We deliver consistent, high-quality Kafka training across regions and time zones for distributed data teams.
Measurable Outcomes
Skills assessments and a capstone platform build show exactly what your team can ship after training.
Build Kafka Streaming Platforms With Reliable Delivery and Observable Processing
Edstellar develops event streaming through Kafka architecture, producer and consumer behavior, cluster resilience, stream processing, and connectors. Teams trace sample events into a live analytics view while testing recovery and schema controls. The final platform review examines delivery assumptions, processing correctness, and monitoring evidence rather than equating continuous data movement with reliability.
- Step 01
Consult
We explore pipeline responsibilities and programming familiarity, identifying gaps in topics and partitions, retry behavior, consumer lag, stream processing, and schema or connector management.
- Step 02
Plan
We establish Kafka architecture before producer-consumer reliability and cluster recovery, then Kafka Streams, Connect, and Schema Registry within the end-to-end analytics platform.
- Step 03
Align
We align Kafka engineering expertise with data engineers, backend developers, and analysts, introducing messaging concepts and adjusting lab support to their programming and database experience.
- Step 04
Customize
We tailor sample order events, database sources, retry cases, and broker failures to relevant streaming workloads, defining volume assumptions and expected processing behavior.
- Step 05
Execute
Teams tune delivery settings, recover broker failures, aggregate event windows, and enforce schemas, receiving feedback on lag, compatibility, stateful processing, and monitoring coverage.
- Step 06
Evaluate
We assess the streaming platform for correct event processing, documented delivery semantics, demonstrated recovery, and dashboards that expose meaningful pipeline health and analytical results.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Event Streaming with Apache Kafka Training Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Event Streaming with Apache Kafka Training for Your Team
Tell us about your team, your streaming stack, and your preferred dates. We will tailor the program and confirm your schedule and trainer.