Corporate Workshops

Technical Training & Workshops

Elevate your engineering team's capabilities with deeply specialized training from highly experienced engineers. Our coaches have extensive experience building large-scale software systems at FAANG and top-tier financial institutions.

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Data Engineering Workshop

Deep dive into building scalable data pipelines, efficient data modeling, and handling massive data volumes in distributed environments.

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Apache Spark

Master the fundamentals of Apache Spark. Learn RDDs, DataFrames, Datasets, and how to write efficient, optimized distributed transformations.

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Apache Flink: Stateful Stream Processing

Move beyond basic pub/sub systems. Learn how to build continuous, stateful streaming applications with sub-millisecond real-time intelligence.

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Modern Java & Spring Boot 3

Shed legacy baggage and leverage modern Java features alongside Spring Boot 3 to build ultra-fast, cloud-native microservices.

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Scala 3 Workshop

Seamlessly transition your team to Scala 3. Master the new syntax, contextual abstractions, and powerful advanced typing features.

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Scala 3 Advanced Functional Programming

Rigorous training on purely functional principles, type-level programming, and category theory concepts applied practically in Scala 3.

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Typed Pekko / Akka Trainings

Master the Actor Model. Learn how to architect, build, and deploy highly concurrent, distributed, and resilient message-driven applications.

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Distributed System Architecture & Observability

Bridge the gap between application development and distributed infrastructure. Design for failures, consensus, and split-brain telemetry.

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AI

Deep dive into large-scale system architectures and integrating LLMs and AI services into highly resilient backend systems.

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Data Engineering Workshop

warning The Engineering Reality: The Single-Node Collapse

Every application starts simple. A single relational database reliably handles your daily gigabytes of application state. Then, the business scales. Suddenly, you are hit with a firehose of real-time telemetry, unyielding clickstreams, or high-frequency financial tick data. Queries that took milliseconds now hang, the CPU pegs at 100%, and the single node simply falls over. You can no longer scale up; you must scale out. This workshop teaches the critical transition from standard CRUD applications to building distributed, fault-tolerant data pipelines capable of processing terabytes of data with sub-second latency.

Architecture & Foundations

Mastering Batch vs. Streaming architectures (Lambda and Kappa patterns) and adapting data models for distributed environments.

Ingestion & Messaging

A deep dive into high-throughput message brokers, exploring Kafka partition strategies, consumer group mechanics, and resilient schema evolution.

Processing & Transformation

Designing robust ELT paradigms that guarantee idempotency and exactly-once processing semantics under heavy load.

Debugging Crucible

A hands-on diagnostic session resolving out-of-order event streams, poison pills, and corrupted data pipelines in a simulated production outage.

Capstone Project

Architecting an end-to-end, low-latency streaming pipeline designed to handle live, high-volume financial or sensor data without dropping packets.

Book Workshop

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Apache Spark

warning The Engineering Reality: The Out-Of-Memory (OOM) Trap

Writing an Apache Spark job is deceptively easy; making it run reliably on a massive dataset is brutally hard. Naïve developers write simple transformations that silently trigger massive network shuffles and severe data skew. The result? Executors die, jobs hang at 99% for hours, and Out-Of-Memory errors plague your cluster. We bypass the basic tutorials to teach you exactly how Spark works under the hood so you can engineer pipelines that actually finish, scaling predictably regardless of data volume.

Distributed Execution

Deconstructing cluster mechanics, the driver/executor model, and the lifecycle of lazy evaluation and action triggers.

Core APIs in Action

Transitioning fluidly between RDDs, DataFrames, and typed Datasets to execute complex window functions, aggregations, and multi-stage joins.

Optimization Under the Hood

Mastering the Catalyst Optimizer and Tungsten execution engine, managing tight partitions, avoiding wide dependencies, and tuning expensive shuffles.

Debugging Crucible

A live triage scenario troubleshooting OOM exceptions, profiling skewed data bottlenecks, and optimizing severe spill-to-disk events.

Capstone Project

Processing, cleaning, and optimizing queries against a massive, highly skewed time-series dataset utilizing advanced partitioning strategies.

Book Workshop

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Apache Flink: Stateful Stream Processing

warning The Engineering Reality: The Real-Time State Crisis

Stateless event routing is easy, and micro-batching works—until you need true, sub-millisecond real-time intelligence. When your business relies on algorithmic trading triggers, live fraud detection, or dynamic pricing, waiting for a batch to process means losing money. The challenge isn't just moving data fast; it's managing complex, historical state accurately across a distributed cluster while guaranteeing exactly-once semantics. This workshop moves teams beyond basic pub/sub systems, teaching them how to build continuous, stateful streaming applications that don't buckle under backpressure.

The Streaming Paradigm

Mastering the fundamental differences between Event Time and Processing Time, and designing robust Watermark strategies to handle out-of-order data.

State Management & Checkpointing

Deep dive into Flink's state backends (like RocksDB), understanding state snapshots, and tuning checkpointing to achieve uncompromised exactly-once guarantees.

Advanced Windowing & CEP

Implementing complex tumbling, sliding, and session windows, alongside Complex Event Processing (CEP) to detect specific behavioral patterns in endless data streams.

Debugging Crucible

A live triage simulation resolving severe backpressure cascades, diagnosing state bloat, and recovering a corrupted pipeline from a failed savepoint.

Capstone Project

Architecting a high-throughput, low-latency live order book aggregator or fraud-detection engine that maintains massive state dynamically.

Book Workshop

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Modern Java & Spring Boot 3

warning The Engineering Reality: The Legacy JVM Anchor

Many enterprises are anchored down by Java 8 codebases, suffering from bloated memory footprints, painful startup times, and convoluted thread-pool management. But Java has quietly undergone a massive revolution. Between Virtual Threads (Project Loom), pattern matching, and native compilation, modern Java is lighter, faster, and more expressive than ever. This workshop is a modernization bootcamp. We teach your team how to shed legacy baggage and leverage Spring Boot 3 alongside cutting-edge JVM features to build ultra-fast, cloud-native microservices.

Modern Language Semantics

Transitioning to modern Java constructs, including Records, Sealed Classes, Pattern Matching, and the functional paradigms introduced in recent LTS releases.

High-Throughput Concurrency

Replacing thread-pool exhaustion with Project Loom; mastering Virtual Threads and Structured Concurrency to handle millions of concurrent connections with minimal memory overhead.

Cloud-Native Spring Boot 3

Building modern microservices with Spring Boot 3, focusing on Ahead-of-Time (AOT) compilation and building native executables using GraalVM.

Debugging Crucible

Identifying and resolving "thread pinning" issues in Virtual Threads, fixing reflection-based crash loops in GraalVM native images, and optimizing JVM garbage collection for low-latency targets.

Capstone Project

Building a cloud-native, sub-second cold-start microservice deployed as a highly optimized GraalVM native image.

Book Workshop

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Scala 3 Workshop

warning The Engineering Reality: The "Implicit Hell" Bottleneck

Your team adopted Scala 2 for its expressive power, but over the years, the codebase has turned into a tangled web of invisible magic. Compile times are dragging, and onboarding new engineers takes months because "implicit hell" makes tracing execution nearly impossible. Scala 3 fundamentally solves this with contextual abstractions, but only if your team knows how to migrate and leverage the new paradigms correctly. This workshop is the bridge to a cleaner, safer, and significantly more productive Scala ecosystem.

Syntax & Core Evolutions

Navigating the streamlined indentation-based syntax, native Enums, export clauses, and mastering Extension Methods for exceptionally clean API design.

Domain-Driven Types

Utilizing intersection/union types and opaque type aliases to model complex business domains exactly, eliminating invalid states at compile time.

Contextual Abstractions

The complete migration path from legacy implicits to explicit, traceable given and using clauses, alongside type class derivation.

Debugging Crucible

An intensive refactoring exercise taking a convoluted Scala 2 codebase and modernizing it to resolve ambiguous givens and hidden dependencies in Scala 3.

Capstone Project

Developing a highly concurrent, robust enterprise REST API that leverages advanced typing to enforce strict domain constraints at compilation.

Book Workshop

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Scala 3 Advanced Functional Programming

warning The Engineering Reality: The Concurrency Nightmare

In highly concurrent environments, traditional object-oriented state mutation is a ticking time bomb. Race conditions, hidden side-effects, and mysterious runtime panics inevitably bleed into production. When a single unhandled exception can crash a critical trading engine or payment gateway, you need mathematical certainty. This workshop elevates engineers from writing Scala as "Java without semicolons" to mastering pure Functional Programming (FP) and Effect Systems, turning runtime terrors into absolute compile-time guarantees.

Pure FP & Category Theory

Grounding your logic in Functors, Applicatives, Monads, and Traverse, ensuring absolute referential transparency.

Effect Systems Deep Dive

Dominating concurrency, resource safety, and error handling using industry-standard libraries like ZIO and Cats Effect.

Advanced Type-Level Programming

Harnessing Generalized Algebraic Data Types (GADTs), Match Types, and dependent typing to make invalid system states fundamentally unrepresentable.

Debugging Crucible

Hunting down and resolving asynchronous space leaks, thread deadlocks, and blocking calls hidden within purely functional workflows.

Capstone Project

Building a high-performance, purely functional matching engine or trading simulator capable of deterministic execution under immense asynchronous pressure.

Book Workshop

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Typed Pekko / Akka Trainings

warning The Engineering Reality: The Blocking Thread Wall

Standard synchronous REST architectures perform wonderfully in testing but choke violently in production. When 100,000 concurrent users hit your system, a traditional backend runs out of operating system threads, leading to cascading timeouts and total service degradation. You cannot solve this by simply buying more servers. The Actor Model fundamentally changes the paradigm, allowing you to process millions of asynchronous messages with a tiny memory footprint, all while maintaining a self-healing architecture that isolates and recovers from failures automatically.

The Typed Actor Model

Shifting to message-driven concurrency, understanding the actor lifecycle, and defining robust, type-safe actor behaviors.

Resilience & Self-Healing

Architecting supervision strategies and fault tolerance to isolate and recover from failures instantly within deeply nested actor hierarchies.

Distributed State & Scaling

Mastering Event Sourcing, CQRS (Command Query Responsibility Segregation) with Persistence, and Cluster Sharding for global scale.

Debugging Crucible

Diagnosing catastrophic network split-brain scenarios, tracing dropped messages across a cluster, and resolving complex distributed deadlocks.

Capstone Project

Engineering a highly distributed, resilient chat server or a high-throughput order routing system capable of sustaining massive message concurrency.

Book Workshop

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Distributed System Architecture & Observability

warning The Engineering Reality: The Physics of Networked Systems

Moving from a monolithic legacy SOA to distributed microservices solves organizational scaling, but it introduces brutal physical realities. Network packets drop, system clocks drift, and nodes die unpredictably. Suddenly, you aren't just writing code; you are negotiating with the CAP theorem. When a multi-tenant PostgreSQL database needs to partition massively, or an algorithmic trading ledger requires strict serializability across a Kafka event stream, basic CRUD knowledge fails. This workshop bridges the gap between application development and distributed infrastructure. We teach your team how to design for Byzantine failures, achieve distributed consensus, and implement the telemetry required to debug a split-brain cluster in seconds.

Storage Engines & Data Structures

Peeling back the database abstraction layer to understand exactly how data is stored and retrieved. Comparing B-Trees against Log-Structured Merge-Trees (LSM-trees) to optimize for heavy read vs. heavy write workloads.

Schema Evolution & Encoding

Architecting for zero-downtime deployments by mastering backward and forward compatibility. Deep dive into binary encoding formats like Protocol Buffers, Avro, and gRPC over standard REST.

Replication & Partitioning (Sharding)

Mastering data distribution. Implementing Single-Leader, Multi-Leader, and Leaderless (Dynamo-style quorum) replication. Designing robust sharding strategies for multi-tenant architectures and handling dynamic rebalancing without dropping traffic.

Transactions & Concurrency Control

Moving beyond basic ACID. Diagnosing complex race conditions like lost updates, write skew, and phantom reads. Understanding Multi-Version Concurrency Control (MVCC) and achieving Serializable Snapshot Isolation (SSI) in high-throughput environments.

The Trouble with Distributed Systems

Surviving the unreliability of networks and clocks. Understanding truth defined by majority, fencing tokens, and the impact of unbounded network delays on system state.

Consistency & Consensus

Achieving distributed agreement. Exploring Linearizability, the limitations of Two-Phase Commit (2PC), and how consensus algorithms like Raft and Paxos underpin critical coordination services (e.g., etcd, Zookeeper).

The Observability Triad

Transitioning from reactive logging to proactive observability. Instrumenting structured logs, high-cardinality metrics, and distributed tracing (OpenTelemetry) to track context across strict network boundaries and asynchronous message brokers.

Debugging Crucible

A live, catastrophic production simulation. Teams must use distributed traces to pinpoint a silent latency spike, diagnose a split-brain scenario in a replicated database, and resolve a distributed deadlock hidden deep within an event queue.

Capstone Project

Architecting a highly available, multi-tenant distributed ledger. The system must guarantee strict serializability, handle dynamic node failures via consensus, and be fully instrumented with 100% end-to-end trace visibility.

Book Workshop

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AI

warning The Engineering Reality: The "Wrapper" Illusion

Building an AI chatbot via a simple API wrapper is a weekend project. Building a secure, enterprise-grade AI system is a profound architectural challenge. When integrating Large Language Models (LLMs) into production, you immediately hit brutal latency spikes, strict context-window limitations, vector database scaling issues, and severe data privacy compliance hurdles. This workshop cuts through the hype, teaching teams how to build deterministic, compliant, and highly reliable agentic architectures that interface securely with your existing legacy systems.

Modern Systems Architecture

Architecting the modernization from legacy SOA to distributed, event-driven microservices designed for AI integration and multi-tenant database scaling.

Data Retrieval & Integration

Engineering robust RAG (Retrieval-Augmented Generation) architectures, scaling vector databases, and managing local LLM inference models for sensitive data.

Agentic Workflows

Implementing the Model Context Protocol (MCP) and safely equipping autonomous AI agents with the tools to query external APIs and internal registries.

Debugging Crucible

Profiling and resolving extreme latency bottlenecks in hybrid infrastructures (traditional backend plus LLM calls) and building programmatic guardrails against hallucinations.

Capstone Project

Designing an enterprise-grade, DPDP-compliant multi-tenant AI support agent that operates securely within strict deterministic guardrails.

Book Workshop

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Next Month's Schedule: Coming Soon

We are currently finalizing dates for our upcoming public and corporate batches. Want to bypass the waitlist and schedule a private, customized workshop exclusively for your team?

Contact Training Team