- Nathan Marz: Principles of Software Engineering, Part 1 - Nathan has worked with Big Data at Twitter and other places and really knows the perils or large, distributed, real-time systems and this post contains plenty of valuable advice for making robust, reliable SW. Main message: "there's a lot of uncertainty in software engineering"; every SW operates correctly only for a certain range of inputs (including volume, HW it runs on, ...) and you never control all of them so there always is an opportunity for failure; you can't predict what inputs you will encounter in the wild. "[..] while software is deterministic, you can't treat it as deterministic in any sort of practical sense if you want to build robust software." "Making software robust is an iterative process: you build and test it as best you can, but inevitably in production you'll discover new areas of the input space that lead to failure. Like rockets, it's crucial to have excellent monitoring in place so that these issues can be diagnosed.". From the content: Sources of uncertainty (bugs, humans, requirements, inputs, ..), Engineering for uncertainty (minimize dependencies, lessen % of cascading failure [JH: -> Hystrix], measure and monitor)
- Suffering-oriented programming is certainly also worth reading (summary: do not start with great designs; only start generalizing and creating libs when you have suffered enough from doing things more manually and thus learned the domain; make it possible > make it beautiful > make it fast, repeat)
- ThoughtWorks open-sources Go, continuous delivery platform - good bye, Jenkins! - better support for pipelines etc., see features and elementary concepts
- Cloud Design Patterns: Prescriptive Architecture Guidance for Cloud Applications (recommended by @markusbk so it must be good); Patterns: Cache-aside, Circuit Breaker, Compensating Transaction, Competing Consumers, Compute Resource Consolidation, Command and Query Responsibility Segregation (CQRS), Event Sourcing, External Configuration Store, Federated Identity, Gatekeeper, Health Endpoint Monitoring, Index Table, Leader Election, Materialized View, Pipes and Filters, Priority Queue, Queue-based Load Leveling, Retry, Runtime Reconfiguration, Scheduler Agent Supervisor, (data) Sharding, Static Content Hosting (-> CDN), Throttling, Valet Key.
Guidance topics: Asynchronous Messaging Primer, Autoscaling, Caching, Compute Partitioning, Data Consistency Primer, Data Partitioning, Data Replication and Synchronization, Instrumentation and Telemetry, Multiple Datacenter Deployment, Service Metering
- MOOC course Functional programming with Clojure at Uni of Helsinki - to get started you need, I suppose, follow the "Material and course content" - essentially read the text for each chapter, clone its repo, submit pull requests to get your work graded
- Jez Humble: The Case for Continuous Delivery - read to persuade manager about CD: "Still, many managers and executives remain unconvinced as to the benefits [of CD], and would like to know more about the economic drivers behind CD." CD reduces waste: "[..]online controlled experiments (A/B tests) at Amazon. This approach created hundreds of millions of dollars of value[..]," reduces risks: "[..] Etsy, has a great presentation which describes how deploying more frequently improves the stability of web services." CD makes development cheaper by reducing the cost of non-value-adding activities such as integration and testing. F.ex. HP got dev. costs down by 40%, dev cost/program by 78%
- Request Quest (via @jraregris) - entertaining and educational intractive quiz regarding what does (not) trigger a request in browsers and differences between them (and deviances from the standard) - img, script, css, etc.
- The REST Statelessness Constraint - a nice post about statelessness in REST if you, like me, don't know REST so much in depth; highlights: Statelesness (and thus the requirement for clients to send their state with every request) is a trade-off crucial for web-scale and partially balanced by caching - while typical enterprise apps have different needs (more state, less scale) so REST isn't a perfect match. Distinguish application (client-side) and server (resources) state. Using a DB to hold the state still violates the requirement. Use links to transfer some state (e.g. contain a link to fetch the next page of records in the response).
- CodeMesh 2013 presentations - good stuff! F.ex. Refactoring Functional Programs: Past and Future, Distribution, Scale and Flexibility with ZeroMQ, Deepak Giridharagopal on Puppet, Immutable Deployments, Analyzing Systems with PuppetDB, Francesco Cesarini and Viktor Klang on the Reactive Manifesto and more
- Cognitive Biases in Times of Uncertainty - people under pressure/stress start to focus on risks over gains and (very) short-term rather than long-term and thus also adopt 0-some mindset (i.e. if sb. else wins, I loose) => polarization into we x them and focus on getting as big piece of the cake possible at any price, now, dismissal of collaboration. With accelerating rate of change in the society due to technology, this is exactly what is happening. How to counter it? Create more positive narratives than the threat-based ones (views of the world), support them via short-term gains. Bottom line: each of us must work on spreading a more positive attitude to save us from bleak future.
- Book - Nathan Marz: Big Data - I dislike the big data hype (and, with passion, Hadoop) but would love to read this book; it presents a fresh look at big data processing, heavily inspired by functional programming. Nathan has plenty of experiences from Twitter and creating Storm and Cascalog (both in Clojure, btw.). Read ch 1: A new paradigm for big data.
- Facebook Engineering: The Mature Optimization Handbook (or go directly to the pdf, ePub, Mobi). If you get bored, jump directly to ch 5. Instrumentation.
Are you benefitting from my writing? Consider buying me a coffee
or supporting my work via GitHub Sponsors. Thank you!