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Software Telemetry: Reliable logging and monitoring [Mīkstie vāki]

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  • Formāts: Paperback / softback, 539 pages, height x width x depth: 234x186x30 mm, weight: 960 g
  • Izdošanas datums: 20-Dec-2021
  • Izdevniecība: Manning Publications
  • ISBN-10: 161729814X
  • ISBN-13: 9781617298141
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  • Cena: 65,11 €
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Software Telemetry: Reliable logging and monitoringPalielināt
  • Formāts: Paperback / softback, 539 pages, height x width x depth: 234x186x30 mm, weight: 960 g
  • Izdošanas datums: 20-Dec-2021
  • Izdevniecība: Manning Publications
  • ISBN-10: 161729814X
  • ISBN-13: 9781617298141
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781617298141.html
Keywords:
Software Telemetry shows you how to efficiently collect, store, and analyze system and application log data so you can monitor and improve your systems.

Summary
In Software Telemetry you will learn how to:

    Manage toxic telemetry and confidential records
    Master multi-tenant techniques and transformation processes
    Update to improve the statistical validity of your metrics and dashboards
    Make software telemetry emissions easier to parse
    Build easily-auditable logging systems
    Prevent and handle accidental data leaks
    Maintain processes for legal compliance
    Justify increased spend on telemetry software

Software Telemetry teaches you best practices for operating and updating telemetry systems. These vital systems trace, log, and monitor infrastructure by observing and analyzing the events generated by the system. This practical guide is filled with techniques you can apply to any size of organization, with troubleshooting techniques for every eventuality, and methods to ensure your compliance with standards like GDPR.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Take advantage of the data generated by your IT infrastructure! Telemetry systems provide feedback on what&;s happening inside your data center and applications, so you can efficiently monitor, maintain, and audit them. This practical book guides you through instrumenting your systems, setting up centralized logging, doing distributed tracing, and other invaluable telemetry techniques.

About the book
Software Telemetry shows you how to efficiently collect, store, and analyze system and application log data so you can monitor and improve your systems. Manage the pillars of observability&;logs, metrics, and traces&;in an end-to-end telemetry system that integrates with your existing infrastructure. You&;ll discover how software telemetry benefits both small startups and legacy enterprises. And at a time when data audits are increasingly common, you&;ll appreciate the thorough coverage of legal compliance processes, so there&;s no reason to panic when a discovery request arrives.

What's inside

    Multi-tenant techniques and transformation processes
    Toxic telemetry and confidential records
    Updates to improve the statistical validity of your metrics and dashboards
    Revisions that make software telemetry emissions easier to parse

About the reader
For software developers and infrastructure engineers supporting and building telemetry systems.

About the author
Jamie Riedesel is a staff engineer at Dropbox with over twenty years of experience in IT.

Table of Contents
1 Introduction
PART 1 TELEMETRY SYSTEM ARCHITECTURE
2 The Emitting stage: Creating and submitting telemetry
3 The Shipping stage: Moving and storing telemetry
4 The Shipping stage: Unifying diverse telemetry formats
5 The Presentation stage: Displaying telemetry
6 Marking up and enriching telemetry
7 Handling multitenancy
PART 2 USE CASES REVISITED: APPLYING ARCHITECTURE CONCEPTS
8 Growing cloud-based startup
9 Nonsoftware business
10 Long-established business IT
PART 3 TECHNIQUES FOR HANDLING TELEMETRY
11 Optimizing for regular expressions at scale
12 Standardized logging and event formats
13 Using more nonfile emitting techniques
14 Managing cardinality in telemetry
15 Ensuring telemetry integrity
16 Redacting and reprocessing telemetry
17 Building policies for telemetry retention and aggregation
18 Surviving legal processes

Recenzijas

The telemetry bible! Sander Zegveld, Developers.nl

An in-depth guide to operating software telemetry systems. Sushant Bhadkamkar, Lyft

A must-have tome of knowledge written by one of the leaders in software telemetry. Andrew Bovill, CACI International Inc

Something for every level of distributed systems, from hardware to networking to operating systems to software. Lokesh Kumar, Urgently

Preface xiii
Acknowledgments xvi
About This Book xviii
About The Author xxiii
About The Cover Illustration xxiv
1 Introduction
1(22)
1.1 Defining the styles of telemetry
4(7)
Defining centralized logging
4(2)
Defining metrics
6(2)
Defining distributed tracing
8(2)
Defining STEM
10(1)
1.2 How telemetry is consumed by different teams
11(4)
Telemetry use by Operations, DevOps, and SRE teams
11(1)
Telemetry use by Security and Compliance teams
12(1)
Telemetry use by Software Engineering and SRE teams
13(1)
Telemetry use by Customer Support teams
13(1)
Telemetry use by business intelligence
14(1)
1.3 Challenges facing telemetry systems
15(5)
Chronic underinvestment harms decision-making
15(2)
Diverse needs resist standardization
17(1)
Information spills and cleaning them up to avoid legal problems
18(1)
Court orders break your assumptions
19(1)
1.4 What you will learn
20(3)
Part 1 Telemetry System Architecture 23(170)
2 The Emitting stage: Creating and submitting telemetry
27(25)
2.1 Emitting from production code
29(14)
Emitting telemetry into a log file
31(2)
Emitting telemetry into the system log
33(4)
Emitting telemetry into standard output
37(3)
Formatting telemetry for emissions
40(3)
2.2 Emitting from hardware
43(4)
Explaining SNMP
43(2)
Ingesting telemetry from a Cisco ASA firewall
45(2)
2.3 Emitting from as-a-Service systems
47(5)
Emitting events from SaaS systems
47(2)
Emitting events from IaaS systems
49(3)
3 The Shipping stage: Moving and storing telemetry
52(22)
3.1 Emitter/shipper functions, telemetry from production code
54(15)
Shipping directly into storage
54(3)
Shipping through queues and streams
57(10)
Shipping to SaaS systems
67(2)
3.2 Shipping between SaaS systems
69(2)
3.3 Tipping points in Shipping-stage architecture
71(3)
4 The Shipping stage: Unifying diverse telemetry formats
74(33)
4.1 Shipping locally-emitted telemetry
75(8)
Shipping telemetry from a log file
76(3)
Shipping telemetry from the system logger
79(2)
Shipping telemetry from standard output
81(2)
4.2 Unifying diverse emitting formats
83(24)
Encoding telemetry into strings
84(5)
Picking a shipping format
89(11)
Converting Syslog to JSON or other object-encoding formats
100(4)
Designing with cardinality in mind
104(3)
5 The Presentation stage: Displaying telemetry
107(31)
5.1 Displaying telemetry in metrics systems
109(9)
Making pretty pictures with telemetry
110(2)
Feeding the graphs with aggregation functions
112(2)
Using aggregations with pdf_pages
114(4)
5.2 Displaying telemetry in centralized logging systems
118(9)
Selecting needed features in a display system for centralized logging
119(2)
Demonstrating centralized logging display
121(6)
5.3 Displaying telemetry in security systems
127(4)
5.4 Displaying telemetry distributed tracing systems
131(4)
5.5 Displaying telemetry in large organizations
135(3)
6 Marking up and enriching telemetry
138(36)
6.1 Markup in the Emitting stage
141(5)
6.2 Markup and enrichment in the Shipping stage
146(16)
Applying context-related telemetry in the Shipping stage
147(3)
Extracting and enriching telemetry in-flight
150(6)
Converting field types during the Shipping stage
156(6)
6.3 Enrichment in the Presentation stage
162(3)
6.4 How telemetry style affects markup and enrichment
165(9)
Markup and enrichment with centralized logging
166(1)
Markup and enrichment with SIEM systems
167(2)
Markup and enrichment with metrics
169(1)
Markup and enrichment with distributed tracing systems
170(4)
7 Handling multitenancy
174(19)
7.1 How multitenant architectures come about
175(5)
Evolving multitenancy in an early-stage startup
175(1)
Evolving multitenancy in a culture of free sharing
176(2)
Evolving multitenancy in a culture of strong separation
178(2)
7.2 Designing multitenant telemetry systems
180(15)
Multitenancy in the Shipping stage
181(8)
Multitenancy in the Presentation stage
189(4)
Part 2 Use Cases Revisited: Applying Architecture Concepts 193(82)
8 Growing cloud-based startup
195(31)
8.1 Telemetry at the small-company stage
197(4)
Describing the small company's telemetry system
198(1)
Analyzing the small company's telemetry system
199(2)
8.2 Telemetry at the medium-size company stage
201(5)
Describing the medium-size company's telemetry system
201(3)
Analyzing the medium-size company's telemetry system
204(2)
8.3 Telemetry at the large-company stage
206(7)
Describing the large company's telemetry system
209(1)
Analyzing the large company's telemetry system
210(3)
8.4 Telemetry at the enterprise stage
213(10)
8.5 Looking back at all this growth
223(3)
9 Nonsoftrvare business
226(22)
9.1 Telemetry use in small organizations
227(3)
9.2 Telemetry use in medium-size organizations
230(3)
9.3 Telemetry use in large organizations
233(6)
9.4 Telemetry use in enterprise organizations
239(9)
10 Long-established business IT
248(27)
10.1 Telemetry use in medium-size organizations
250(5)
Telemetry use in office IT
251(3)
Telemetry use in production systems
254(1)
10.2 Telemetry use in large organizations
255(7)
10.3 Telemetry use in global organizations
262(15)
Telemetry use in the Booking and Passenger Manifest department
265(4)
Telemetry use in the Loyalty Programs department
269(6)
Part 3 Techniques For Handling Telemetry 275(212)
11 Optimizing for regular expressions at scale
277(30)
11.1 Anchoring expressions for speed
279(6)
11.2 Building expressions to fail fast
285(5)
11.3 Digging into the Cisco ASA firewall telemetry
290(7)
11.4 Refining emissions to speed regular-expression performance
297(8)
11.5 Additional regular-expression resources
305(2)
12 Standardized logging and event formats
307(28)
12.1 Implementing structured logging in your code
309(5)
12.2 Implementing standards in your code
314(11)
12.3 Implementing standards in the Shipping stage
325(10)
13 Using more nonfile emitting techniques
335(22)
13.1 Designing for socket- and datagram-based emitters
336(8)
13.2 Emitting and shipping for container- and serverless-based code
344(6)
Emitting and shipping from containerd-based code
345(2)
Emitting and shipping from serverless-based code
347(3)
13.3 Encrypting UDP-based telemetry
350(7)
14 Managing cardinality in telemetry
357(27)
14.1 Identifying cardinality problems
359(7)
Cardinality in time-series databases
360(4)
Cardinality in logging databases
364(2)
14.2 Lowering the cost of cardinality
366(18)
Use logging standards to contain cardinality
366(7)
Using storage-side methods to tame cardinality
373(6)
Make cardinality someone else's problem
379(5)
15 Ensuring telemetry integrity
384(27)
15.1 Getting telemetry out of reach of an attacker
386(8)
Move telemetry too fast to catch
386(3)
Use ACLs to enforce write- only telemetry
389(4)
Durable telemetry when using SaaS providers
393(1)
15.2 Making telemetry harder to mess with
394(17)
Using access control requirements to defend against attacks
395(2)
Ensuring configuration integrity in your telemetry systems
397(3)
Making changes obvious
400(11)
16 Redacting and reprocessing telemetry
411(28)
16.1 Identifying toxic data and where it comes from
412(4)
16.2 Redacting toxic information spills
416(7)
16.3 Reprocessing telemetry to support upgrades
423(6)
16.4 Isolating toxic data to reduce cleanup costs
429(10)
17 Building policies for telemetry retention and aggregation
439(24)
17.1 Creating a retention policy
440(8)
Building a policy for centralized logging
443(2)
Building a policy for metrics
445(1)
Building a policy for distributed tracing
446(1)
Building a policy for STEM systems
447(1)
17.2 Creating an aggregation policy
448(9)
17.3 Using sampling to reduce costs and increase retention
457(6)
18 Surviving legal processes
463(24)
18.1 Defining the eDiscovery process
466(3)
18.2 Dealing with records-retention requests
469(8)
Examining an ELK-based centralized logging system
471(3)
Examining a Sumo Logic-based centralized logging system
474(3)
18.3 Dealing with document-production requests
477(5)
Telemetry in the collection phase
478(2)
Telemetry in the review phase
480(1)
Telemetry in the production phase
481(1)
18.4 Working with lawyers
482(5)
Appendix A Telemetry Storage Systems 487(12)
Appendix B Recommendation Checklist Reference 499(21)
Appendix C Exercise Answers 520(5)
Index 525
Jamie Riedesel is a staff engineer at Dropbox. She has over twenty years of experience in IT, working in government, education, legacy companies, and startups. She has specialized in DevOps for the past decade, running distributed systems in public clouds, getting over workplace trauma, and designing software telemetry architectures.