The Bip-Buffer is like a circular buffer, but slightly different. Instead of keeping one head and tail pointer to the data in the buffer, it maintains two revolving regions, allowing for fast data access without having to worry about wrapping at the end of the buffer. Buffer allocations are always maintained as contiguous blocks, allowing the buffer to be used in a highly efficient manner with API calls, and also reducing the amount of copying which needs to be performed to put data into the buffer. Finally, a two-phase allocation system allows the user to pessimistically reserve an area of buffer space, and then trim back the buffer to commit to only the space which was used..

Prototypes give rise to a broad spectrum of interesting technical, conceptual and philosophical issues. In this paper we take a rather unusual, non-technical approach and investigate object-oriented programming and the prototype-based programming field from a purely philosophical viewpoint. Some historical facts and observations pertaining to objects and prototypes are presented, and conclusions based on those observations are derived

E propose a simple yet expressive storage model, termed Parametric I/O Model (PIO) that captures contemporary devices by parameterizing read/write asymmetry(α)and access concurrency(k). PIO enables device-specific decisions at algorithm design time, rather than as an optimization during deployment and testing, thus ensuring optimal algorithm design by taking into account the properties of each device.

The Ribbon filter is a new data structure that is more space-efficient than the popular Bloom filters that are widely used for optimizing data retrieval.

Cyclomatic Complexity was initially formulated as a measurement of the “testability and maintainability” of the control flow of a module.While it excels at measuring the former , its underlying mathematical model is unsatisfactory at producing a value that measures the latter. This white paper describes a new metric that breaks from the use of mathematical models to evaluate code in order to remedy Cyclomatic Complexity’s shortcomings and produce a measurement that more accurately reflects the relative difficulty of understanding,and therefore of maintaining methods, classes, and applications

This paper makes an eccentric proposal: clients can write without waiting, then wait for durability before reading. This doesn’t prevent data loss, but it does guarantee that clients never read data that is lost subsequently. Add a further guarantee that the system replies to each query with data at least as fresh as its previous reply, no matter which client is querying it, and you get a quirky new consistency property: “cross-client monotonic reads”.

AIP stands for API Improvement Proposal, which is a design document providing high-level, concise documentation for API development. They are to serve as the source of truth for API-related documentation at Google and the means by which API teams discuss and come to consensus on API guidance

We propose a distributed protocol for a queue, called \textsc{Skueue}, which spreads its data fairly onto multiple processes, avoiding bottlenecks in high throughput scenarios. \textsc{Skueue} can be used in highly dynamic environments, through the addition of join and leave requests to the standard queue operations enqueue and dequeue. Furthermore \textsc{Skueue} satisfies sequential consistency in the asynchronous message passing model. Scalability is achieved by aggregating multiple requests to a batch, which can then be processed in a distributed fashion without hurting the queue semantics. Operations in \textsc{Skueue} need a logarithmic number of rounds w.h.p. until they are processed, even under a high rate of incoming requests.

We introduce PathQuery, a graph query language developed to scale with Google's query and data volumes as well as its internal developer community. PathQuery supports flexible and declarative semantics. We have found that this enables query developers to think in a naturally "graphy" design space and to avoid the additional cognitive effort of coordinating numerous joins and subqueries often required to express an equivalent query in a relational space. Despite its traversal-oriented syntactic style, PathQuery has a foundation on a custom variant of relational algebra -- the exposition of which we presently defer -- allowing for the application of both common and novel optimizations. We believe that PathQuery has withstood a "test of time" at Google, under both large scale and low latency requirements. We thus share herein a language design that admits a rigorous declarative semantics, has scaled well in practice, and provides a natural syntax for graph traversals while also admitting complex graph patterns

Serverless computing has emerged as an attractive deployment option for cloud applications in recent times. The unique features of this computing model include, rapid auto-scaling, strong isolation, fine-grained billing options and access to a massive service ecosystem which autonomously handles resource management decisions. This model is increasingly being explored for deployments in geographically distributed edge and fog computing networks as well, due to these characteristics. Effective management of computing resources has always gained a lot of attention among researchers. The need to automate the entire process of resource provisioning, allocation, scheduling, monitoring and scaling, has resulted in the need for specialized focus on resource management under the serverless model. In this article, we identify the major aspects covering the broader concept of resource management in serverless environments and propose a taxonomy of elements which influence these aspects, encompassing characteristics of system design, workload attributes and stakeholder expectations. We take a holistic view on serverless environments deployed across edge, fog and cloud computing networks. We also analyse existing works discussing aspects of serverless resource management using this taxonomy. This article further identifies gaps in literature and highlights future research directions for improving capabilities of this computing model.

This post describes how we empowered our millions of users at Canva to collaborate at scale by introducing services that support bidirectional streaming using RSocket.

Run a real Postgres database locally on Linux, OSX or Windows as part of another Go application or test.

Locality-sensitive hashing (LSH) is a set of techniques that dramatically speed up search-for-neighbors or near-duplication detection on data. These techniques can be used, for example, to filter out duplicates of scraped web pages at an impressive speed, or to perform near-constant-time lookups of nearby points from a geospatial data set

CurveCP is similar to TCP but uses high-speed high-security elliptic-curve cryptography to protect every packet against espionage, corruption, and sabotage. The cryptographic tools used in CurveCP are the same as the cryptographic tools used in DNSCurve. CurveCP was announced at the 27th Chaos Communication Congress on 28 December 2010.

We describe metastable failures—a failure pattern in distributed systems. Currently, metastable failures manifest themselves as black swan events; they are outliers because nothing in the past points to their possibility, have a severe impact, and are much easier to explain in hindsight than to predict. Although instances of metastable failures can look different at the surface, deeper analysis shows that they can be understood within the same framework.We introduce a framework for thinking about metastable failures, apply it to examples observed during years of operating distributed systems at scale, and survey ad-hoc techniques developed post-factum for making systems resilient to known metastable failures. A systematic approach for building systems that are robust against unknown metastable failures remains an open problem

We observe that widely deployed NICs possess scatter-gather capabilities that can be re-purposed to accelerate serialization’s core task of coalescing and flattening in-memory data structures. It is possible to build a completely zero-copy,zero-allocation serialization library with commodity NICs.Doing so introduces many research challenges, including using the hardware capabilities efficiently for a wide variety of non-uniform data structures, making application memory available for zero-copy I/O, and ensuring memory safety

In this paper, we propose contextual concurrency control(C3), a new paradigm that enables userspace applications to tune concurrency control in the kernel.C3allows developers to change the behavior and parameters of kernel locks, to switch between different lock implementations and to dynamically profile one or multiple locks for a specific scenario of interest.

Kernel-bypass networking, which allows applications to circumvent the kernel and interface directly with NIC hardware,is one of the main tools for improving application network performance. However, allowing applications to circumvent the kernel makes it impossible to use tools (e.g.,tcpdump) or impose policies (e.g., QoS and filters) that need to interpose on traffic sent by different applications running on a host.This makes maintainability and manageability a challenge for kernel-bypass applications. In response, we propose Kernel On-Path Interposition (KOPI), in which traditional kernel data-plane functionality is retained but implemented in a fully programmable SmartNIC. We hypothesize that KOPI can support the same tools and policies as the kernel stack while retaining the performance benefits of kernel bypass

We argue that network virtualization as experienced by many cloud tenants is overly complex and needs to be rethought.We propose that the goal for a new design should be to free cloud tenants entirely from having to build and operate virtual networks. Building on this philosophy, we propose that instead of low-level building blocks (virtual links, routers,firewalls), cloud networking should be exposed to tenants in a declarative and endpoint-centric manner

The Syndicated Actor model is a new model of concurrency, closely related to the actor, tuplespace, and publish/subscribe models.

PatchELF is a simple utility for modifying existing ELF executables and libraries

We present a fully lock-free variant of the recent Montage system for persistent data structures. Our variant, nbMontage, adds persistence to almost any nonblocking concurrent structure without introducing significant overhead or blocking of any kind. Like its predecessor, nbMontage is buffered durably linearizable: it guarantees that the state recovered in the wake of a crash will represent a consistent prefix of pre-crash execution. Unlike its predecessor, nbMontage ensures wait-free progress of the persistence frontier, thereby bounding the number of recent updates that may be lost on a crash, and allowing a thread to force an update of the frontier (i.e., to perform a sync operation) without the risk of blocking. As an extra benefit, the helping mechanism employed by our wait-free sync significantly reduces its latency. Performance results for nonblocking queues, skip lists, trees, and hash tables rival custom data structures in the literature -- dramatically faster than achieved with prior general-purpose systems, and generally within 50% of equivalent non-persistent structures placed in DRAM.

With the ever-increasing dataset sizes, several file formats like Parquet, ORC, and Avro have been developed to store data efficiently and to save network and interconnect bandwidth at the price of additional CPU utilization. However, with the advent of networks supporting 25-100 Gb/s and storage devices delivering 1, 000, 000 reqs/sec the CPU has become the bottleneck, trying to keep up feeding data in and out of these fast devices. The result is that data access libraries executed on single clients are often CPU-bound and cannot utilize the scale-out benefits of distributed storage systems. One attractive solution to this problem is to offload data-reducing processing and filtering tasks to the storage layer. However, modifying legacy storage systems to support compute offloading is often tedious and requires extensive understanding of the internals. Previous approaches re-implemented functionality of data processing frameworks and access library for a particular storage system, a duplication of effort that might have to be repeated for different storage systems. In this paper, we introduce a new design paradigm that allows extending programmable object storage systems to embed existing, widely used data processing frameworks and access libraries into the storage layer with minimal modifications. In this approach data processing frameworks and access libraries can evolve independently from storage systems while leveraging the scale-out and availability properties of distributed storage systems. We present one example implementation of our design paradigm using Ceph, Apache Arrow, and Parquet. We provide a brief performance evaluation of our implementation and discuss key results.

Modern online services rely on data stores that replicate their data across geographically distributed data centers. Providing strong consistency in such data stores results in high latencies and makes the system vulnerable to network partitions. The alternative of relaxing consistency violates crucial correctness properties. A compromise is to allow multiple consistency levels to coexist in the data store. In this paper we present UniStore, the first fault-tolerant and scalable data store that combines causal and strong consistency. The key challenge we address in UniStore is to maintain liveness despite data center failures: this could be compromised if a strong transaction takes a dependency on a causal transaction that is later lost because of a failure. UniStore ensures that such situations do not arise while paying the cost of durability for causal transactions only when necessary. We evaluate UniStore on Amazon EC2 using both microbenchmarks and a sample application. Our results show that UniStore effectively and scalably combines causal and strong consistency.

Tuning a PID controller can be easily done using a systematic procedure. We just put it in a web application. No more trial and error.

Recently, TiDB 5.0 takes a big step to greatly reduce the latency of transaction commits—introducing the Async Commit feature. This article describes Async Commit's design ideas and its key implementation details.

In-memory key-value stores are critical components that help scale large internet services by providing low-latency access to popular data. Memcached, one of the most popular key-value stores, suffers from performance limitations inherent to the Linux networking stack and fails to achieve high performance when using high-speed network interfaces. While the Linux network stack can be bypassed using DPDK based solutions, such approaches require a complete redesign of the software stack and induce high CPU utilization even when client load is low. To overcome these limitations, we present BMC, an in-kernel cache for Memcached that serves requests before the execution of the standard network stack. Requests to the BMC cache are treated as part of the NIC interrupts, which allows performance to scale with the number of cores serving the NIC queues. To ensure safety, BMC is implemented using eBPF. Despite the safety constraints of eBPF, we show that it is possible to implement a complex cache service. Because BMC runs on commodity hardware and requires modification of neither the Linux kernel nor the Memcached application, it can be widely deployed on existing systems. BMC optimizes the processing time of Facebook-like small-size requests. On this target workload, our evaluations show that BMC improves throughput by up to 18x compared to the vanilla Memcached application and up to 6x compared to an optimized version of Memcached that uses the SO_REUSEPORT socket flag. In addition, our results also show that BMC has negligible overhead and does not deteriorate throughput when treating non-target workloads.

In Function as a Service (FaaS), a serverless computing variant, customers deploy functions instead of complete virtual machines or Linux containers. It is the cloud provider who maintains the runtime environment for these functions. FaaS products are offered by all major cloud providers (e.g. Amazon Lambda, Google Cloud Functions, Azure Functions); as well as standalone open-source software (e.g. Apache OpenWhisk) with their commercial variants (e.g. Adobe I/O Runtime or IBM Cloud Functions). We take the bottom-up perspective of a single node in a FaaS cluster. We assume that all the execution environments for a set of functions assigned to this node have been already installed. Our goal is to schedule individual invocations of functions, passed by a load balancer, to minimize performance metrics related to response time. Deployed functions are usually executed repeatedly in response to multiple invocations made by end-users. Thus, our scheduling decisions are based on the information gathered locally: the recorded call frequencies and execution times. We propose a number of heuristics, and we also adapt some theoretically-grounded ones like SEPT or SERPT. Our simulations use a recently-published Azure Functions Trace. We show that, compared to the baseline FIFO or round-robin, our data-driven scheduling decisions significantly improve the performance.

Edge computing as a promising technology provides lower latency, more efficient transmission, and faster speed of data processing since the edge servers are closer to the user devices. Each edge server with limited resources can offload latency-sensitive and computation-intensive tasks from nearby user devices. However, edge computing faces challenges such as resource allocation, energy consumption, security and privacy issues, etc. Auction mechanisms can well characterize bidirectional interactions between edge servers and user devices under the above constraints in edge computing. As demonstrated by the existing works, auction and mechanism design approaches are outstanding on achieving optimal allocation strategy while guaranteeing mutual satisfaction among edge servers and user devices, especially for scenarios with scarce resources. In this paper, we introduce a comprehensive survey of recent researches that apply auction approaches in edge computing. Firstly, a brief overview of edge computing including three common edge computing paradigms, i.e., cloudlet, fog computing and mobile edge computing, is presented. Then, we introduce fundamentals and backgrounds of auction schemes commonly used in edge computing systems. After then, a comprehensive survey of applications of auction-based approaches applied for edge computing is provided, which is categorized by different auction approaches. Finally, several open challenges and promising research directions are discussed

Litestream is a standalone streaming replication tool for SQLite. It runs as a background process and safely replicates changes incrementally to another file or S3.

The goal of Landlock is to enable to restrict ambient rights (e.g. global filesystem access) for a set of processes. Because Landlock is a stackable LSM, it makes possible to create safe security sandboxes as new security layers in addition to the existing system-wide access-controls. This kind of sandbox is expected to help mitigate the security impact of bugs or unexpected/malicious behaviors in user space applications. Landlock empowers any process, including unprivileged ones, to securely restrict themselves

A library to do type-safe and low-boilerplate bit level serialization

We present a federated, asynchronous, memory-limited algorithm for online task scheduling across large-scale networks of hundreds of workers. This is achieved through recent advancements in federated edge computing that unlocks the ability to incrementally compute local model updates within each node separately. This local model is then used along with incoming data to generate a rejection signal which reflects the overall node responsiveness and if it is able to accept an incoming task without resulting in degraded performance. Through this innovation, we allow each node to execute scheduling decisions on whether to accept an incoming job independently based on the workload seen thus far. Further, using the aggregate of the iterates a global view of the system can be constructed, as needed, and could be used to produce a holistic perspective of the system. We complement our findings, by an empirical evaluation on a large-scale real-world dataset of traces from a virtualized production data center that shows, while using limited memory, that our algorithm exhibits state-of-the-art performance. Concretely, it is able to predict changes in the system responsiveness ahead of time based on the industry-standard CPU-Ready metric and, in turn, can lead to better scheduling decisions and overall utilization of the available resources. Finally, in the absence of communication latency, it exhibits attractive horizontal scalability.

As distributed systems grow in scale and complexity, the need for flexible automation of systems management functions also grows. We outline a framework for building tools that provide distributed, scalable, declarative, modular, and continuous automation for distributed systems. We focus on four points of design: 1) a state-management approach that prescribes source-of-truth for configured and discovered system states; 2) a technique to solve the declarative unification problem for a class of automation problems, providing state convergence and modularity; 3) an eventual-consistency approach to state synchronization which provides automation at scale; 4) an event-driven architecture that provides always-on state enforcement. We describe the methodology, software architecture for the framework, and constraints for these techniques to apply to an automation problem. We overview a reference application built on this framework that provides state-aware system provisioning and node lifecycle management, highlighting key advantages. We conclude with a discussion of current and future applications

Modern web applications heavily rely on in-memory key-value caches to deliver low-latency, high-throughput services. In-memory caches store small objects of size in the range of 10s to 1000s of bytes, and use TTLs widely for data freshness and implicit delete. Current solutions have relatively large per-object metadata and cannot remove expired objects promptly without incurring a high overhead. We present Segcache, which uses a segment-structured design that stores data in fixed-size segments with three key features: (1) it groups objects with similar creation and expiration time into the segments for efficient expiration and eviction, (2) it approximates some and lifts most per-object metadata into the shared segment header and shared information slot in the hash table for object metadata reduction, and (3) it performs segment-level bulk expiration and eviction with tiny critical sections for high scalability. Evaluation using production traces shows that Segcache uses 22-60% less memory than state-of-the-art designs for a variety of workloads. Segcache simultaneously delivers high throughput, up to 40% better than Memcached on a single thread. It exhibits close-to-linear scalability, providing a close to 8× speedup over Memcached with 24 threads.

Our take is that you should use systemd-resolved, and if you need user-friendly network configuration, a very recent version of NetworkManager (1.26.6 or better). This will give your distro state-of-the-art DNS capabilities, and make implementers of networking software much happier

Quorum systems are a powerful mechanism for ensuring the consistency of replicated data. Production systems usually opt for majority quorums due to their simplicity and fault tolerance, but majority quorum systems provide poor throughput and scalability. Alternatively, researchers have invented a number of theoretically "optimal" quorum systems, but the underlying theory ignores many practical complexities such as machine heterogeneity and workload skew. In this paper, we conduct a pragmatic re-examination of quorum systems. We enrich the current theory on quorum systems with a number of practical refinements to find quorum systems that provide higher throughput, lower latency, and lower network load. We also develop a library Quoracle that precisely quantifies the available trade-offs between quorum systems to empower engineers to find optimal quorum systems, given a set of objectives for specific deployments and workloads. Our tool is available online at: https://github.com/mwhittaker/quoracle.

Framework for evaluating (planet-scale) consensus protocols Tempo, Atlas, EPaxos, FPaxos, Caesar, Janus

Unikraft automatically builds extremely efficient and secure software. By tailoring the operating system, libraries and tools to the particular needs of your application, it vastly reduces virtual machine and container image sizes to a few KBs, drastically cutting down your software stack's attack surface

Modern web applications replicate their data across the globe and require strong consistency guarantees for their most critical data. These guarantees are usually provided via state-machine replication (SMR). Recent advances in SMR have focused on leaderless protocols, which improve the availability and performance of traditional Paxos-based solutions. We propose Tempo - a leaderless SMR protocol that, in comparison to prior solutions, achieves superior throughput and offers predictable performance even in contended workloads. To achieve these benefits, Tempo timestamps each application command and executes it only after the timestamp becomes stable, i.e., all commands with a lower timestamp are known. Both the timestamping and stability detection mechanisms are fully decentralized, thus obviating the need for a leader replica. Our protocol furthermore generalizes to partial replication settings, enabling scalability in highly parallel workloads. We evaluate the protocol in both real and simulated geo-distributed environments and demonstrate that it outperforms state-of-the-art alternatives.

Maelstrom is a workbench for learning distributed systems by writing your own. It uses the Jepsen testing library to test toy implementations of distributed systems. Maelstrom provides standardized tests for things like "a commutative set" or "a transactional key-value store", and lets you learn by writing implementations which those test suites can exercise.

[A] simple mechanism for detection of uninitialized reads in userspace with minimal performance overhead

Leaders make decisions that set context for further decisions. They enable something strategic, but also constrain and shape —but only as essential to system outcomes. And decisions that cross contexts or boundaries, need leadership —to help others understand the need and outcomes, and consequences, and what their role is in making the decision effective. Leaders communicate strategic intent and decisions, and foster organizational will and goodwill, to facilitate work towards coherent strategic outcomes.

We can easily build accurate monitoring for all traffic in only 40 lines of code for bpftrace.

A small object optimization for polymorphic types is a very useful construct so it important to understand how it can be done correctly.

In the course of trying to figure out how to smoothly zoom timelines of a billion trace events, I figured out a cool tree structure that I can’t find elsewhere online, which it turned out two of my friends have independently derived after not finding anything on their own searches. It’s a way of implementing an index for doing range aggregations on an array (e.g “find the sum/max of elements [7,12]”) in O(log N) time, with amortized constant time appends, a simple implementation (around 50 lines of Rust), low constant factors, and low memory overhead.

Recent years have seen Kubernetes emerge as a primary choice for container orchestration. Kubernetes largely targets the cloud environment but new use cases require performant, available and scalable orchestration at the edge. Kubernetes stores all cluster state in etcd, a strongly consistent key-value store. We find that at larger etcd cluster sizes, offering higher availability, write request latency significantly increases and throughput decreases similarly. Coupled with approximately 30% of Kubernetes requests being writes, this directly impacts the request latency and availability of Kubernetes, reducing its suitability for the edge. We revisit the requirement of strong consistency and propose an eventually consistent approach instead. This enables higher performance, availability and scalability whilst still supporting the broad needs of Kubernetes. This aims to make Kubernetes much more suitable for performance-critical, dynamically-scaled edge solutions.

Wuffs is a memory-safe programming language (and a standard library written in that language) for wrangling untrusted file formats safely. Wrangling includes parsing, decoding and encoding. Example file formats include images, audio, video, fonts and compressed archives

Over the years, platforms and application requirements change. As they do, technologies come, go, and return again as the preferred solution to certain system problems. In each of its incarnations, the technology’s details change but the principles remain the same. One such technology is distributed transactions on middle-tier servers. Here, we argue that after a 15-year decline, they need to return to the mainstream

This is a C++ class library for using the Single Instruction Multiple Data (SIMD) instructions to improve performance on modern microprocessors with the x86 or x86/64 instruction set on Windows, Linux, and Mac platforms. There are no plans to support ARM or other instruction sets.

When it comes to having durable data, there are four ways to do it: undo log, redo log, shadow copy and shadow data.

High-resolution timers and a few oddities in the way the x86_64 emulation on the M1 presents itself, that lead to some potential “gotchas”.

There are a lot of different application-layer protocols, and it seems they all end up evolving solutions to many of the same problems. This article seeks to identify the aspects of functionality commonly found in many application-layer protocol, and serves as a dictionary of those functions.

Cuckoo Index (CI) is a lightweight secondary index structure that represents the many-to-many relationship between keys and partitions of columns in a highly space-efficient way. At its core, CI associates variable-sized fingerprints in a Cuckoo filter with compressed bitmaps indicating qualifying partitions.

A clear picture of the hidden algorithm that runs for every function call at compile time.

EBPFSnitch is a Linux Application Level Firewall based on eBPF and NFQUEUE. It is inspired by OpenSnitch, and Douane, but utilizing modern kernel abstractions, without a kernel module. The eBPFSnitch daemon is implemented in C++ 20. The control interface is implemented in Python 3 utilizing Qt5

Smaller cells offer lower availability in the face of small numbers of uncorrelated node failures, but better availability when the proportion of node failure exceeds 50%. While such high failure rates are rare, they do happen in practice

CRAQ is a replication protocol that allows reads from any replica while still maintaining strong consistency. CRAQ should provide better read throughput than Raft and Paxos. Read performance grows linearly with the number of nodes added to the system. Network chatter is significantly lower compared to Raft and Paxos.

Serverless is an increasingly popular choice for service architects because it can provide elasticity and load-based billing with minimal developer effort. A common and important use case is to compose serverless functions and cloud storage into reliable workflows. However, existing solutions for authoring workflows provide a rudimentary experience compared to writing standard code in a modern programming language. Furthermore, executing workflows reliably in an elastic serverless environment poses significant performance challenges. To address these, we propose Durable Functions, a programming model for serverless workflows, and Netherite, a distributed execution engine to execute them efficiently. Workflows in Durable Functions are expressed as task-parallel code in a host language of choice. Internally, the workflows are translated to fine-grained stateful communicating processes, which are load-balanced over an elastic cluster. The main challenge is to minimize the cost of reliably persisting progress to storage while supporting elastic scale. Netherite solves this by introducing partitioning, recovery logs, asynchronous snapshots, and speculative communication. Our results show that Durable Functions simplifies the expression of complex workflows, and that Netherite achieves lower latency and higher throughput than the prevailing approaches for serverless workflows in Azure and AWS, by orders of magnitude in some cases.

Replicated Object Notation (RON) is a format for distributed live data. RON’s primary mission is continuous data synchronization. A RON object may naturally have any number of replicas, which may synchronize in real-time or intermittently. JSON, protobuf, and many other formats implicitly assume serialization of separate state snapshots. RON has versioning and addressing metadata, so state and updates can be always pieced together. RON handles state and updates all the same: state is change and change is state.

It is a good idea to equip yourself with at least a basic understanding of lockless primitives. Throughout this series I will describe what acquire and release semantics are really about, and present five relatively simple patterns that alone can cover most uses of the primitives.

Rasmussen’s migration model illustrates that small optimizations and adaptations can accumulate over time, taking the system far from its initial design parameters. If there is no counterweight to this “practical drift” from operations staff who are alert to the possibility and the dangers of the normalization of deviance, from the safety function, or from an effective regulator, systems are likely to drift towards catastrophe.

Fully managed, horizontally scalable, multitenant, persistent distributed priority queue built on top of sharded MySQL that enables developers at Facebook to decouple and scale microservices and distributed systems.

Vendor-neutral log-linear histograms for the compression, mergeability, and analysis of telemetry data

I often declare these kinds of wars on unneeded copies and allocations. Talking to the global allocator is not exactly cheap and making extra copies is just not elegant. Sometimes it means using a bump allocator, or even writing an extension for it. Sometimes it means extensive use of borrowing.

This technique optimizes the expressiveness of the call site at the expense of the one of the interface and implementation. Indeed, the interface needs naming and a comment to help clarify how to use it, and the implementation has more code to turn the parameters around.

Get started with your own BPF application quickly and painlessly with libbpf-bootstrap scaffolding, which takes care of all the mundane setup steps and lets you dive right into BPF fun and minimize the necessary boilerplate. We'll take a look at what libbpf-bootstrap provides and how everything is tied together.

Linux has a mechanism that can turn asynchronous signals into synchronous events that can be handled by epoll. It’s a great idea, really. If signals can be delivered via a file descriptor, much like data, then existing I/O multiplexing mechanisms like epoll can be used to handle signals much like we handle other file descriptors that represent local files or sockets. This is exactly the idea behind Linux’s signalfd(2) system call

This article will describe thread-local storage on ELF platforms in detail, and touch on other related topics, such as: thread-specific data keys and Windows/macOS TLS.

Here’s a problem. I have a set of keys and values. I also have some servers for a key-value store. This could be memcached, Redis, MySQL, whatever. I want to distribute the keys across the servers so…