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Performance Engineering and System Design Handbook
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Chapters
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01
The Performance Contract
27:50
02
Workload Models: Describe the Demand Before the System
27:53
03
Objectives, Indicators, and Budgets
29:37
04
Quantities, Units, and the Laws That Pay Rent
31:08
05
Distributions, Variance, and Tail Behavior
31:25
06
Queues, Utilization, and Backpressure
28:35
07
Bottlenecks, Constraints, and Causal Diagnosis
32:16
08
The Performance-Aware System Design Loop
28:05
09
CPU Execution: From Instructions to Useful Work
20:29
10
Memory Hierarchy, Locality, and NUMA
30:00
11
Scheduling, Threads, and Concurrency Runtimes
32:00
12
Allocation, Garbage Collection, and Managed Runtimes
36:04
13
Storage Media and I/O Paths
35:21
14
Networks, Protocols, and the Cost of Distance
42:09
15
Virtualization, Containers, and Cloud Variability
40:34
16
Accelerators, Heterogeneous Compute, and Energy
42:27
17
Data Layout, Algorithms, and Locality
39:06
18
Parallelism, Synchronization, and Contention
42:37
19
Asynchronous Execution, Queues, and Backpressure
41:51
20
Batching, Pipelining, Vectorization, and Amortization
41:45
21
Caching as a Consistency and Capacity Design
53:59
22
Serialization, Compression, and Protocol Shape
52:21
23
Load Balancing and Work Placement
40:22
24
Admission Control, Rate Limiting, and Load Shedding
40:59
25
Deadlines, Timeouts, Retries, Hedging, and Idempotency
43:12
26
Partitioning, Sharding, Skew, and Rebalancing
43:55
27
Replication, Quorums, and Read/Write Paths
39:46
28
Consistency, Coordination, and Transaction Boundaries
44:09
29
API, Schema, and Data-Contract Design for Performance
43:41
30
Service Topology and Critical-Path Design
47:06
31
Messaging, Logs, and Delivery Semantics
35:05
32
Event Processing, Idempotent Effects, and ‘Exactly Once’
40:22
33
Time, Ordering, Identity, and Causality
44:30
34
Partial Failure, Tail Amplification, and Recovery
44:56
35
Geo-distribution and the Physics of Distance
44:40
36
Elasticity, Autoscaling, and Control Loops
46:29
37
Multi-tenancy, Isolation, and Fairness
40:18
38
State Placement, Ownership, and Derived Data
41:09
39
Low-Latency Request/Response Services
42:24
40
Transactional Systems and OLTP
45:22
41
Key-Value Stores and Distributed Caches
40:33
42
Event Ingestion and Stream Processing
42:36
43
Batch, Analytical, and Data-Warehouse Systems
32:51
44
Search, Indexing, and Retrieval Systems
34:44
45
Object, File, Media, and CDN Systems
32:13
46
Real-Time Fan-out, Presence, and Collaboration
31:32
47
ML and AI Inference Systems
32:50
48
Edge, Mobile, and Intermittently Connected Systems
37:04
49
Observability as a Performance Instrument
27:36
50
Profiling Across CPU, Memory, I/O, Locks, and Distributed Traces
32:49
51
Benchmarking and Microbenchmarking
30:50
52
Load, Stress, Spike, Soak, and Resilience Testing
39:17
53
Experimental Design and Performance Statistics
37:38
54
Capacity Planning and Demand Forecasting
42:43
55
Analytical Models and Queueing Networks
43:33
56
Simulation, Trace Replay, and What-If Analysis
44:11
57
Performance Regression Prevention and Continuous Validation
35:18
58
Performance Incident Response
45:53
59
The Optimization Workflow: From Hypothesis to Durable Gain
30:37
60
Deployment, Rollout, and Online Migration
31:17
61
Resilience Under Overload and Recovery
29:41
62
Cost, Efficiency, and Sustainable Performance
34:00
63
Security, Privacy, and Performance Trade-offs
28:31
64
Performance Design Reviews and Decision Records
30:47
65
Ownership, Culture, and the Performance Program
33:02
66
Case Study: Restoring a Latency SLO in a High-Throughput API
62:13
67
Case Study: Multi-Region Ordering and Payment
27:54
68
Case Study: The Hot-Key Cache Collapse
34:33
69
Case Study: A Burst-Tolerant Event Pipeline
55:22
70
Case Study: Deadline-Aware Search and Autocomplete
58:53
71
Case Study: Multi-Tenant Interactive Analytics
55:41
72
Case Study: Cost-Constrained AI Inference
60:23
73
Case Study: Zero-Downtime Storage and Schema Migration
42:22
74
Case Study: Anatomy of an Overload Incident
42:53
