# partition Published articles for partition. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Architecting a secure landing zone in the AWS European Sovereign Cloud DevFeed: [Architecting a secure landing zone in the AWS European Sovereign Cloud]() Original publisher: [Read original article]() Author: Pablo Pagani Published: 2026-09-16T21:20:48Z Content type: article Language: en Sources: [AWS Security Blog]() Topics: [Amazon Web Services](), [Cloud](), [Architecture & Design](), [AWS IAM](), [Infrastructure as code](), [CI/CD](), [SIEM, Security](), [Incident response]() Tags: [advanced-300](), [aws](), [aws-identity-and-access-management-iam](), [ci-cd](), [cloud](), [eu](), [europe](), [incident-response](), [infrastructure-as-code-iac](), [partition](), [security](), [security-blog](), [security-identity-compliance](), [technical-how-to]() ### AI overview This article explains how to architect a secure, scalable landing zone in the AWS European Sovereign Cloud. It describes the aws-eusc partition boundary and covers governance, identity, logging, data protection, network design, CI/CD, artifact distribution, and incident response. ### Source excerpt The AWS European Sovereign Cloud is a new, independent cloud for Europe, physically and logically separate from existing AWS Regions and operated within the European Union (EU). It provides the same services, features, and APIs as AWS commercial Regions, but runs as a distinct AWS partition (aws-eusc), with its own control plane, AWS Identity and [...] ## "Regex for Rows": Simplifying Pattern Detection in SQL with MATCH\_RECOGNIZE DevFeed: ["Regex for Rows": Simplifying Pattern Detection in SQL with MATCH\_RECOGNIZE]() Original publisher: [Read original article]() Author: Kent Marten; Sergei Fedorov Published: 2026-09-16T17:14:05Z Content type: tutorial Language: en Sources: [Databricks]() Topics: [SQL](), [databricks](), [Cybersecurity](), [Security & Privacy]() Tags: [count](), [cybersecurity](), [databricks](), [failed](), [false-positives](), [functions](), [login](), [partition](), [product](), [real-time](), [regex](), [sql](), [window-functions]() ### AI overview This tutorial explains how Databricks supports SQL MATCH_RECOGNIZE for detecting ordered event patterns. It shows how the clause can simplify sequence detection, including identifying repeated login failures followed by a successful login, compared with complex SQL queries and window functions. ### Source excerpt Imagine you work in cybersecurity and you have a table that tracks login attempts... ## How We Built Automated Capacity Testing for Kafka Consumers DevFeed: [How We Built Automated Capacity Testing for Kafka Consumers]() Original publisher: [Read original article]() Author: Kaan Karakaya Published: 2026-09-14T09:46:34Z Content type: tutorial Language: en Sources: [Booking.com Development - Medium]() Topics: [Kafka](), [Testing](), [HTTP]() Tags: [automated](), [capacity](), [health-checks](), [kafka](), [load](), [load-balancer](), [parallelism](), [partition](), [recovery](), [scale](), [site-reliability-engineer](), [sre](), [testing]() ### AI overview This article describes Booking.com's extension of an existing capacity-testing platform for Kafka consumers. It explains how changing partition assignment can provide a controlled, measurable way to test consumer throughput and whether remaining consumers can absorb reassigned work after an instance or failure domain disappears. ### Source excerpt Photo by GuerrillaBuzz on Unsplash Kafka makes it easy to distribute work across consumer instances. It is much harder to prove, safely and repeatedly, how those instances behave when the distribution changes and one of them has to carry more than its usual share. For teams that run Kafka at scale, this is a practical reliability question: how much load can a consumer instance actually handle? We had automated capacity testing for HTTP services, but Kafka consumers were still tested with manual drills. Those drills could tell us something, but they were disruptive, difficult to reproduce, and risky precisely when the system was close to its limit. We wanted a controlled way to answer three questions: What is the maximum sustainable throughput of a consumer instance? If an instance or failure domain disappears, can the remaining consumers absorb the reassigned work? Are we overprovisioning resources because we do not know the real limit? The result was an extension to our capacity-testing platform that turns Kafka partition assignment into a safe, measurable load-control mechanism. Why HTTP capacity testing did not translate Our existing platform was designed for request-response services behind a load balancer. A scheduled test selects one instance, routes an increasing share of traffic to it, runs health checks after each step, and records the highest ratio the instance can sustain. After the test, traffic returns to its normal distribution and the result is reported to the service owner. Kafka has no equivalent traffic knob. Consumers pull records, and the unit of parallelism is the partition. Within a consumer group, each partition is owned by one consumer at a time. If a topic has 12 partitions and four equally loaded instances, each instance owns about three. When one instance disappears, a rebalance gives the survivors more partitions -- and the extra work arrives as a step change, not as a smooth increase from a load balancer. The key translation: for an HTTP ## Linux swap Commands: Create and Manage Swap Files/Partitions DevFeed: [Linux swap Commands: Create and Manage Swap Files/Partitions]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-08-26T15:13:53Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [btrfs](), [Kernel](), [rhel]() Tags: [blog](), [btrfs](), [commands](), [desktop](), [files](), [fstab](), [gotchas](), [guide](), [how-to](), [linux](), [partition](), [performance](), [server](), [sysadmins]() ### AI overview A practical guide to creating, activating, deactivating, and troubleshooting Linux swap files and partitions using mkswap, swapon, and swapoff. It also explains filesystem-specific considerations, including Btrfs and older XFS kernels. ### Source excerpt A practical guide to creating, managing, and tuning swap files and swap partitions on Linux using mkswap, swapon, and swapoff, with real commands and common troubleshooting fixes. Continue reading... ## Where Kafka Fits in Modern Systems DevFeed: [Where Kafka Fits in Modern Systems]() Original publisher: [Read original article]() Author: Nikki Siapno Published: 2026-08-25T12:02:09Z Content type: tutorial Language: en Sources: [Level Up Coding System Design Newsletter]() Topics: [Kafka](), [Event-Streaming](), [systems](), [distributed-systems](), [data]() Tags: [architecture](), [consumer](), [distributed-systems](), [durability](), [event-streaming](), [kafka](), [parallelism](), [partition](), [pipelines](), [real-time](), [systems]() ### AI overview This article explains when Apache Kafka is appropriate for distributed systems. It presents Kafka as a durable event log whose replayability, consumer fan-out, and partition-based parallelism support real-time data pipelines and shared event-driven architectures, while warning that Kafka can add unnecessary operational complexity for simpler asynchronous workflows. ### Source excerpt When should you actually use Kafka? And when is it just unnecessary complexity? ## How to Set Up Hibernation on Linux (Swap Done Right) DevFeed: [How to Set Up Hibernation on Linux (Swap Done Right)]() Original publisher: [Read original article]() Author: Hayden James Published: 2026-08-24T15:11:25Z Content type: tutorial Language: en Sources: [Hayden James]() Topics: [Linux](), [Kernel](), [Debian](), [xfce]() Tags: [archlinux](), [blog](), [debian](), [desktop](), [distro](), [hibernate](), [how-to](), [kernel](), [linux](), [memory](), [partition](), [rhel](), [xfce]() ### AI overview A practical Linux hibernation guide explains how to use separate swap spaces for everyday paging and hibernation. It addresses a problem where a swap partition becomes too full to hold the compressed hibernation image. ### Source excerpt I recently reinstalled my main desktop from scratch: Debian testing via Kali underneath (read first before judging) and XFCE on top. One of the reasons I keep coming back to XFCE is its built-in power management. Continue reading... ## How to Achieve Pruning When Querying by Non-Partitioned Columns in PostgreSQL DevFeed: [How to Achieve Pruning When Querying by Non-Partitioned Columns in PostgreSQL]() Original publisher: [Read original article]() Author: Haki Benita Published: 2026-07-08T21:00:00Z Content type: tutorial Language: en Sources: [Haki Benita]() Topics: [PostgreSQL](), [Databases]() Tags: [articles](), [how-to](), [index](), [partition](), [patterns](), [performance](), [postgresql](), [query]() ### AI overview This tutorial explains PostgreSQL partition pruning and shows how certain data patterns can enable pruning when queries filter on columns other than the partition key. It uses event data partitioned by year and examines queries by date range and session. ### Source excerpt Under conventional wisdom, pruning can only be achieved when querying by the partition key. However, if your data follows certain patterns, using some clever tricks you can achieve pruning even when filtering by non-partition key columns. ## Lightweight deletes for Tinybird Data Sources now in Beta DevFeed: [Lightweight deletes for Tinybird Data Sources now in Beta]() Original publisher: [Read original article]() Author: Jesús Botella Published: 2026-06-30T12:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [clickhouse](), [data]() Tags: [clickhouse](), [data](), [partition](), [product-updates]() ### AI overview Tinybird has added a beta endpoint for ClickHouse lightweight DELETE operations. It supports synchronous deletion and asynchronous deletion with polling for partition progress. ### Source excerpt A new endpoint exposes ClickHouse's lightweight DELETE functionality in Tinybird: pick between a synchronous call that blocks until the delete is done, or an asynchronous one that you poll for partition progress. ## How Partition Access Visualizations Reduced our Data Lake S3 Cost by 33% DevFeed: [How Partition Access Visualizations Reduced our Data Lake S3 Cost by 33%]() Original publisher: [Read original article]() Author: Nick Del Nano, Data Streaming Published: 2026-05-21T00:00:00Z Content type: article Language: en Sources: [Yelp]() Topics: [data](), [data lake](), [Apache Iceberg](), [Amazon S3](), [AWS IAM]() Tags: [analytics](), [apache-iceberg](), [aws](), [data](), [data-lake](), [iam](), [partition](), [s3]() ### AI overview Yelp describes visualizations that map partition keys against access-event timestamps to reveal daily batch jobs, backfills, and ad hoc queries. The resulting usage attribution supported Apache Iceberg migration and storage-efficiency work that reduced the cost of its petabyte-scale data lake by 33%. ### Source excerpt Introduction In large analytics environments, data teams often struggle to answer deceptively simple questions, like who their stakeholders are and how their data is being used. At Yelp, we address this by visualizing access patterns, plotting time-based partition key values against access event timestamps. These visualizations reveal distinct usage signatures - ad hoc queries, daily batch jobs, and periodic backfills - allowing data owners to understand their stakeholders and use cases. This deeper insight into data usage has enabled high-impact platform initiatives including migrating thousands of tables to Apache Iceberg format and identifying storage efficiencies which reduced the cost of... ## How Split Brain Happens in Distributed Databases and How It Gets Fixed DevFeed: [How Split Brain Happens in Distributed Databases and How It Gets Fixed]() Original publisher: [Read original article]() Published: 2026-03-31T00:00:00Z Content type: tutorial Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Databases](), [Network](), [Replication](), [CAP theorem]() Tags: [consensus](), [databases](), [distributed](), [failed](), [false-positives](), [partition](), [replication](), [split-brain]() ### AI overview This tutorial explains how split brain occurs in distributed databases when a network partition causes multiple nodes to become primary and accept conflicting writes. It discusses why timeout-based failure detection can create false positives and introduces the distributed consensus complexity motivated by this failure mode. ### Source excerpt . [How Split Brain Happens in Distributed Databases and How It Gets Fixed](split-brain-in-distributed-databases-cover... ## Databricks is abstracting away physical data engineering controls DevFeed: [Databricks is abstracting away physical data engineering controls]() Original publisher: [Read original article]() Author: Zach Wilson Published: 2026-02-24T01:03:11Z Content type: opinion Language: en Sources: [DataExpert.io Newsletter]() Topics: [databricks](), [data-engineering](), [Apache Iceberg](), [Open Source]() Tags: [architecture](), [data-engineering](), [databricks](), [open-source](), [partition](), [partitioning](), [sorting](), [spark]() ### AI overview This opinion article argues that Databricks is shifting away from hands-on data engineering by abstracting physical data modeling through features such as liquid clustering and predictive optimization. It also criticizes Databricks' support for managed Apache Iceberg tables after acquiring Tabular. ### Source excerpt Databricks abstracts away almost all of the data engineering skills. Liquid clustering is the first place where things will get messy! ## Waiting for PostgreSQL 19 - Implement ALTER TABLE ... MERGE/SPLIT PARTITIONS ... command DevFeed: [Waiting for PostgreSQL 19 - Implement ALTER TABLE ... MERGE/SPLIT PARTITIONS ... command]() Original publisher: [Read original article]() Author: depesz Published: 2026-01-04T17:30:47Z Content type: opinion Language: en Sources: [select \* from depesz;]() Topics: [PostgreSQL](), [function]() Tags: [command](), [locking](), [merge](), [partition](), [partitioning](), [partitions](), [pg19](), [postgresql](), [split](), [uncategorized](), [waiting]() ### AI overview A PostgreSQL 19 development update describes the ALTER TABLE command for merging and splitting partitions. The patch was rolled back after earlier discussion, then recommitted; testing showed it worked as expected, with slightly less locking observed. Further changes may be needed before the feature reaches the final release. ### Source excerpt Important update This has been rolled back after some discussion. On 14th of December 2025, Alexander Korotkov committed patch: Implement ALTER TABLE ... MERGE PARTITIONS ... command This new DDL command merges several partitions into a single partition of the target table. The target partition is created using the new createPartitionTable() function with the ... Continue reading "Waiting for PostgreSQL 19 - Implement ALTER TABLE ... MERGE/SPLIT PARTITIONS ... command" ## How to Fix Kafka to ClickHouse® Performance Bottlenecks DevFeed: [How to Fix Kafka to ClickHouse® Performance Bottlenecks]() Original publisher: [Read original article]() Author: Alberto Romeu Published: 2025-12-30T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Kafka](), [Optimization](), [Structured-data]() Tags: [best-practices](), [clickhouse](), [distribution](), [how-to](), [kafka](), [optimization](), [partition](), [performance](), [pipeline](), [scalable-analytics-architecture](), [schema](), [view]() ### AI overview A tutorial on optimizing performance in Kafka-to-ClickHouse pipelines through schema optimization, Materialized View tuning, partition distribution strategies, and throughput practices. ### Source excerpt Learn how to optimize your Kafka to ClickHouse pipeline performance with schema optimization, Materialized View tuning, partition distribution strategies and throughput best practices. ## Waiting for PostgreSQL 19 - Support COPY TO for partitioned tables. DevFeed: [Waiting for PostgreSQL 19 - Support COPY TO for partitioned tables.]() Original publisher: [Read original article]() Author: depesz Published: 2025-10-22T10:05:08Z Content type: article Language: en Sources: [select \* from depesz;]() Topics: [PostgreSQL](), [data]() Tags: [command](), [copy](), [partition](), [partitioning](), [partitions](), [performance](), [pg19](), [postgresql](), [uncategorized](), [waiting]() ### AI overview The article discusses a PostgreSQL patch committed by Masahiko Sawada that adds direct COPY TO support for partitioned tables. Previously, users had to use COPY (SELECT ...) TO as a workaround. The author's test found similar performance, with COPY from a table slightly slower in the reported case. ### Source excerpt On 20th of October 2025, Masahiko Sawada committed patch: Support COPY TO for partitioned tables. Previously, COPY TO command didn't support directly specifying partitioned tables so users had to use COPY (SELECT ...) TO variant. This commit adds direct COPY TO support for partitioned tables, improving both usability and performance. Performance tests show ... Continue reading "Waiting for PostgreSQL 19 - Support COPY TO for partitioned tables." ## Designing a Cloud-Native Event Log Beyond Kafka's Partition Model DevFeed: [Designing a Cloud-Native Event Log Beyond Kafka's Partition Model]() Original publisher: [Read original article]() Published: 2025-04-24T14:25:00Z Content type: opinion Language: en Sources: [Gunnar Morling]() Topics: [Kafka](), [Amazon S3](), [cloud-infrastructure](), [event driven](), [systems]() Tags: [agentic](), [cloud-native](), [event-driven](), [event-sourcing](), [kafka](), [partition](), [pipelines](), [s3]() ### AI overview The article proposes a personal wishlist for a durable cloud-native event log designed beyond Kafka's traditional architecture. It discusses separating storage and compute, using object storage such as S3, removing partitions, and providing key-centric streams with ordering and dynamically scalable consumers. ### Source excerpt The last few days I spent some time digging into the recently announced KIP-1150 ("Diskless Kafka"), as well AutoMQ's Kafka fork, tightly integrating Apache Kafka and object storage, such as S3. Following the example set by WarpStream, these projects aim to substantially improve the experience of using Kafka in cloud environments, providing better elasticity, drastically reducing cost, and paving the way towards native lakehouse integration. This got me thinking, if we were to start all over and develop a durable cloud-native event log from scratch--Kafka.next if you will--which traits and characteristics would be desirable for this to have? Separating storage and compute and object store support would be table stakes, but what else should be there? Having used Kafka for many years for building event-driven applications as well as for running realtime ETL and change data capture pipelines, here's my personal wishlist: ## Introducing the Tinybird DynamoDB Connector in public beta DevFeed: [Introducing the Tinybird DynamoDB Connector in public beta]() Original publisher: [Read original article]() Author: Cameron Archer Published: 2024-09-20T00:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [DynamoDB]() Tags: [dynamodb](), [partition](), [product-updates]() ### AI overview Tinybird's DynamoDB Connector has entered public beta, enabling cross-partition queries in milliseconds. ### Source excerpt The DynamoDB Connector just hit public beta. Cross-partition queries in milliseconds are now possible. Test it yourself. ## How to switch between multiple ESP32 firmware binaries stored in the flash memory DevFeed: [How to switch between multiple ESP32 firmware binaries stored in the flash memory]() Original publisher: [Read original article]() Author: John Lee Published: 2024-07-24T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [Microcontroller](), [Embedded Software Dev](), [Internet of things](), [ESP32-S3](), [m5stack](), [Wokwi]() Tags: [binaries](), [blog](), [boot](), [bootloader](), [bsp](), [build](), [code](), [embedded](), [embedded-systems](), [esp32](), [esp32-p4](), [esp32-s3](), [espressif](), [firmware](), [flash](), [gui](), [how-to](), [iot](), [m5stack](), [memory](), [ota](), [partition](), [quick-start](), [releases](), [simulation](), [wokwi]() ### AI overview A tutorial on using the ESP32 Graphical Bootloader to store multiple firmware images in flash memory and switch between them. It explains the bootloader flow, partition-table configuration, and steps for building, merging, flashing, and simulating the application. ### Source excerpt Introduction# The ESP32 microcontroller is a versatile and powerful device, widely used in IoT and embedded applications. One of its advanced features is the ability to store multiple firmware images in its flash memory and switch between them. This capability can be leveraged for various purposes, such as testing different firmware versions, running multiple applications, or maintaining a backup firmware. ## 1st-stage GUI setup, Part 3 - December 2023: First tests DevFeed: [1st-stage GUI setup, Part 3 - December 2023: First tests]() Original publisher: [Read original article]() Published: 2024-02-01T00:00:00Z Content type: article Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [GUI](), [Testing](), [Code]() Tags: [bootloader](), [code](), [free](), [gui](), [iso](), [open-source](), [os](), [partition](), [react](), [reactos](), [tests](), [win32](), [winapi]() ### AI overview This third post in the ReactOS "1st-stage GUI setup" series describes December 2023 work testing the complete graphical installer with a partially Wine-synced setupapi DLL. It covers partition-management UI behavior, the all-in-one CD ISO test scenario, installation dialogs, hardware presets, and current limitations to initialized MBR disks, with GPT and uninitialized-disk support planned. ### Source excerpt Greetings! Welcome to the third blog of the series "1st-stage GUI setup": September 2023: Partly Wine-syncing setupapi October-November 2023: Making partitioning UI work December 2023: First tests In this third blog post, I will cover my work done during the month of December 2023: testing the whole 1st-stage GUI setup, together with the partially wine-synced setupapi dll. Finishing and testing the partitioning page UI The first week was devoted to finally putting together the code for manipulating partitions from the user interface, using the new workflow, and testing it. ## Understanding How DynamoDB Scales DevFeed: [Understanding How DynamoDB Scales]() Original publisher: [Read original article]() Author: Guillermo Ojeda Published: 2023-10-19T14:40:53Z Content type: tutorial Language: en Sources: [Guille Ojeda]() Topics: [NoSQL](), [Database](), [Serverless](), [Availability](), [Resilience](), [Transactions](), [Provisioning]() Tags: [architecture](), [availability](), [aws](), [databases](), [distributed](), [dynamodb](), [nosql](), [partition](), [provisioning](), [resilience](), [serverless](), [transactions]() ### AI overview This tutorial explains how DynamoDB scales horizontally through partitioning and replication across nodes. It compares provisioned capacity for reads and writes and explains read and write capacity units, consistency, data size limits, and the doubled capacity use of transactions. ### Source excerpt Note: This content was originally published at the Simple AWS newsletter. As you probably know, DynamoDB is a NoSQL database. It's a managed, serverless service, meaning you just create a Table (that's the equivalent of a Database in Postgres), and A... ## Hermès Bélusca-Maïto hired full-time to work on the ReactOS GUI Setup DevFeed: [Hermès Bélusca-Maïto hired full-time to work on the ReactOS GUI Setup]() Original publisher: [Read original article]() Published: 2023-10-01T00:00:00Z Content type: news Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [GUI]() Tags: [bare-metal](), [bootloader](), [community](), [free](), [gui](), [open-source](), [os](), [partition](), [react](), [reactos](), [registry](), [team](), [virtual-machines](), [win32](), [winapi]() ### AI overview ReactOS Deutschland e.V. hired Hermès Bélusca-Maïto to work full-time for five months on the ReactOS GUI Setup. The planned work includes completing setup functionality, adding GPT support, integrating registry callbacks, and making other refinements. ### Source excerpt Our team proudly announces that ReactOS Deutschland e.V. has hired Hermès Bélusca-Maïto to work full-time on the ReactOS GUI Setup for the next 5 months, starting September 2, 2023. Hermès is a long-time contributor and developer who worked on the project since 2012. He has several skills and expertise into various components of ReactOS, notably being the Client/Server Runtime Subsystem (CSRSS), Console Server Subsystem (CONSRV), NTVDM, and others. His upcoming goal is to finish the first-stage ReactOS GUI setup, which offers an alternative to the classic first-stage text-mode setup (also called USETUP). ## Vertical vs. horizontal scaling: What's the difference and which is better? DevFeed: [Vertical vs. horizontal scaling: What's the difference and which is better?]() Original publisher: [Read original article]() Author: Charlie Custer Published: 2023-04-10T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [autoscaling](), [Cloud](), [Database](), [Server]() Tags: [cloud](), [database](), [gcp](), [partition](), [scale](), [server](), [work]() ### AI overview The article compares vertical scaling, which increases the capacity of existing machines, with horizontal scaling, which adds machines or nodes. It explains examples using cloud databases and notes that the better approach depends on the system and workload; scaling terminology can also be used imprecisely. ### Source excerpt So you need to scale. That's a good problem to have! But should you scale up or scale out? There's no easy answer, so let's take a closer look at horizontal scaling vs. vertical scaling , how they compare, and what the pros and cons are for each approach. ## OTA Firmware Updates with ESP Privilege Separation DevFeed: [OTA Firmware Updates with ESP Privilege Separation]() Original publisher: [Read original article]() Author: John Lee Published: 2023-01-29T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-IDF](), [Embedded Software Dev]() Tags: [blog](), [business-logic](), [esp](), [esp-idf](), [esp-privilege-separation](), [esp32](), [firmware](), [firmware-update](), [iot](), [ota](), [partition](), [security](), [updates]() ### AI overview This article explains independent over-the-air firmware updates for protected_app and user_app in ESP Privilege Separation. It describes the ESP-IDF partition layout, the user-app update workflow, background downloading, reboot handling, and optional signature verification. ### Source excerpt Over-The-Air (OTA) firmware update is one of the most important feature of any connected device. It enables the developers to ship out new features and bug fixes by remotely updating the application. In ESP Privilege Separation, there are two applications -- protected_app and user_app for which the framework provides the ability to independently update both the application binaries. In this post we will describe the independent OTA update feature under ESP Privilege Separation. ## Migrating Kafka topics without downtime DevFeed: [Migrating Kafka topics without downtime]() Original publisher: [Read original article]() Published: 2022-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Kafka](), [ordering](), [Scalability](), [version]() Tags: [downtime](), [kafka](), [ordering](), [partition](), [versioning]() ### AI overview A tutorial for migrating Kafka topics by creating versioned replacement topics, redirecting publishers and consumers, and draining the old topics. It explains how partition counts affect ordering, concurrency, scalability, and management overhead, and notes that the author did not find a direct tool for migration without downtime. ### Source excerpt Each kafka topic defines the number of partitions and replication factors when it's created. However, once a topic is created, the partition count cannot be changed without affecting the ordering guarantees of the kafka partitions since kafka uses the following formula to calculate which partition a record should go to: partition\_id = partition\_key % number of partitions Kafka partitions are the gateway to concurrency and scalability... ## How to use custom partition tables on ESP32 DevFeed: [How to use custom partition tables on ESP32]() Original publisher: [Read original article]() Author: John Lee Published: 2021-02-12T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [Embedded Software Dev](), [configuration]() Tags: [blog](), [bluetooth](), [bootloader](), [esp-idf](), [esp32](), [espressif](), [firmware](), [flash](), [how-to](), [iot](), [ota](), [partition](), [storage](), [wifi]() ### AI overview This tutorial explains how ESP32 flash memory is organized and how custom partition tables can separate application firmware from persistent data. It references ESP-IDF v4.2 and discusses partitions used for configuration, calibration, WiFi and Bluetooth data, and OTA updates. ### Source excerpt Introduction# When we create a new project using ESP32 , sometimes we need to store data in the flash to persist even after a restart or power down. In the past, the most common way to do that was by using EEPROM, with just a few bytes of storage ability which limited it for larger amount of data. On the other hand, the ESP32 uses a flash memory to store the firmware, including the bootloader and other relevant data. [Next page]()