Coder Legion - Recent posts tagged storage

The Decentralized Storage Revolution: Exploring SIA's Tech Exploring S3 gateway with Sia's renterd.

Mon, 24 Aug 2026 20:38:05 +0000

The Decentralized Storage Revolution: Exploring SIA’s Cutting Edge Technology.

Table Of Contents

Brief about SIA
Rivals in the industry
Exclusiveness of SIA
Security of SIA protocol.
Enters Renterd.
Renterd’s user interface.
Storage Utility.
Notable Improvement made by Renterd.
SIA’s S3-compatible gateway.
Ways Renterd could be used with S3.
Interplanetary File System.
Sharing a data file.
Benefits of SIA’s decentralized storage technology.
Reference.

Brief about SIA

Launched in 2015, Sia protocol curved out an enviable name in decentralized storage cloud storage ecosystem. It is a secure and trustless blockchain protocol, amongst the first, to integrate the principle of idle storage space leasing to users in its mechanism, making it the pioneer layer zero storage chain in the crypto sphere.
Sia has several innovative products and services which include Hostd, Walletd and Renterd. Users in need of storage spaces are provided same on a rental basis. Sia’s utility is powered by its own token, Siacoin (SC).Founded by David Vorick and Luke Champine, Sia is named after the god of perception in ancient Egypt and has weathered the storm in the competitive world of blockchain technology.

Rivals in the industry

At the time that Sia was founded, it emerged as a notable rival to the likes of Google, Microsoft, Apple and amazon which are centralized storage systems up to this day. In like manner, several other companies like Bitquery, Zap3, and Footprint analytics are Sia’s competitors today. This is good for decentralization and Innovation.

Exclusiveness of SIA

Sia distinguished itself from existing centralized storage structures by its decentralized mechanism which enhanced lower rates of internet storage facility. A synergy between leasers and renters of storage space has streamlined a special kind of peer to peer business relationship implemented by Sia’s immutable and trustless smart contract technology.
In place of fiat currency which is the norm with traditional hubs, the use of Siacoin as the choice of payment created a utility need in the Sia network. In terms of its storage mechanism, Sia utilizes encrypted files which are stored in 30 fragments and each fragment hosted across the world. In the common day parlance, is said to utilize the shard technology.

Security of Sia protocol

Like Bitcoin, the safety of the Sia protocol is guaranteed by proof of work consensus where the majority of workers are required to approve a mined block in addition to an intense mining competition among them.
Collaterals are required of decentralized computers wanting to host on the Sia protocols and this requirement safeguards the protocol against their intentions to defraud or attack the network.
The segregation of encrypted files into 30 fragments also protect the protocol in the eventuality of a natural disaster as there is the unlikelihood of a natural disaster happening simultaneously across the world where these segments are hosted.

Enters Renterd

Having been a robust network through progressive development and research, Sia is up with Renterd, a new software, galvanized for storage app developers and storage space users. Developed by the Sia foundation, Renterd succeeded Siad which was the previous data renting software utilized by Sia protocol since her inception.
Renterd is meant to improve on Siad’s performance even though it was built from the ground up. It remedied scalability, flexibility, usability and interface issues that were found wanting in Siad. In the area of scalability, Renterd is integrated with a horizontal scalability which consist of an autopilot, a bus and a worker; each of these components has an API.
However, all the 3 apparatuses can defaultedly function as a single unit or separately by customization. The autopilot integrates communication with the bus and the worker. The bus encompasses all the codes and the worker manages task-related communication with the hosting nodes.

Renterd’s User Interface.

The user interface in Renterd is designed to be web-friendly and with authentication features, making it handy for devices and by remote means. Through the employment of metrics, chronological data can be viewed. The user interface has a placement of an alert system where users and host nodes are timely informed about current events in the Sia network, a deviation from the status quo with Siad where users had to login before they can access relevant network communication.
Developers outside the Sia network can also integrate with Sia webhook API to customize their own environment alert systems such as chat bots. Sia’ Renterd is crafted for compatibility with S3, a standardized cloud storage platform and through the use of APIs, users can now store their data on Sia network as a cloud folder or file without having to resort to the use of disks.

Storage Utility.

Storage utility has not been left out in Renterd’s design. To minimize storage waste, Renterd comes with a dual feature to improve storage efficiency: contract pruning and built-in upload packing. In the era of Siad, users’ data were inerasable and this means continuous storage cost.
Also by default, files as small as 1kb , are amplified or padded to a size of 40MB before being uploaded and this is obviously unproductive With Renterd, the integration of these two storage utility features now make storage cost less expensive, expands utility and eliminates waste.

Notable Improvement made by Renterd

Workers can now extract files via uploading and downloading in a single effective process.
Utilization of an array of SQL databases to erase downtime on the network, thus improving usability for large industries and single users.
User and remote friendly interface which is made possible by Bus hosting.
Establishment of node health surveillance unswervingly from the user interface.
Implementation of Sia-Amazon S3 compatibility and integration.
Waste mitigation through the use of built-in upload packing and contract pruning.
Promotion of privacy through enhanced encryption.

Sia’s S3-compatible gateway.

It’s mentioned how Renterd was designed for compatibility with S3 which is a simple storage service developed by amazon web services in 2006. S3 is a storage service that employs cloud technology. It stores myriad forms of data ranging from analytics to web applications. It has a robust encryption which protects users from privacy intrusion through control mechanisms such as buckets, access control lists (ACLs) and identity and access management (IAM).
Ways Renterd could be used with S3.
Renterd could be used as an IPFS data reservoir in the absence of a tangible space. Backing up files onto Sia’s grid using S3 responsive gears and setting up an object container (Bucket) locally as a dossier are extra ways which users can use Sia’s S3 compatible gateway.

Interplanetary File System.

IFPS is a file sharing technological structure that utilizes encrypted and decentralized distribution mechanism. It is the abbreviated form for Interplanetary file system. To share a data in a peer to peer mode, the user is required to install and activate a node. IFPS gateways are needed and set up to increase the web availability of IFPS.
Each IFPS node set up is carried using Renterd, a plugin and an IFPS gateway before making it available for public. The public gateway also needs a Renterd server, a domain name and a web server. First, the potential user needs to set up Renterd followed by S3 gateway and a public gateway.

Sharing a data file.

When these set ups are effectively running, the user shares data by way of uploading or downloading. To do this, he should access Sia website and generate storage space after funding Sia wallet with Siacoin. Then, he needs to launch Sia gateway on his S3 gateway and generate object buckets before sharing a file.
The flow of file sharing are reversal for uploading and downloading. The former requires files to be transferred to Sia from a server where they have been momentarily stockpiled and the upload completion cycle is reached when the redundancy level is 1x. Sia then amplifies the redundancy threshold to 10x. The reverse is the case when files are being downloaded (from Sia to S3 and public servers). Both process flows utilize encryption and only permitted users can access any shared file.

Benefits of Sia’s decentralized storage technology

Decentralized storage technology enhances data security, maintains user’s privacy, supplants the monopoly of gigantic data industries, promotes sufficient control on one’s data, reduces the frequent risks of data violations, makes uploaded data readily available, checks unlawful access to data, mitigate abuse of data.

Conclusion

The Sia protocol and its accessories have proven to be pliable, useful, and viable. With approximately a decade of operation, it has explored and curated a data sharing and storage software packed with tested innovative features which are compatible with S3 portal.
Decentralized data storage systems are here to stay. In an epoch characterized by authoritative control by centralized institutions and counter forces of democracy, privacy and freedom, Sia’s decentralized storage projects shall remain relevant in the blockchain ecosystem.

Reference

Alphagrowth (2023). Top 6 Sia competitors andalternatives.https://alphagrowth.io/siacoin/competitors
Bitdegree (2023)What is amazon S3. https://www.bitdegree.org/crypto/learn/crypto-terms/what-is-amazon-s3
Coinweb (2024).What is Amazon S3? https://coinweb.com/wiki/amazon-s3/
Devpost (2023) Renterd Innovate https://renterdinnovate2023.devpost.com/?utm_source=devpost&utm_medium=alert&utm_campaign=20231222_allinterest
Herbert, Z. (2017) Introducing S3-style file sharing for Sia through the new minio integration. https://blog.sia.tech/introducing-s3-style-file-sharing-for-sia-through-the-new-minio-integration-bb880af2366a
Ink, S. (2023) Sia S3 Integration: IPFS. Creating a public IPFS gateway backed by Sia https://blog.sia.tech/sia-s3-integration-ipfs-ac9f50fb3a5d
Ink, S.(2023) The state of Sia. https://blog.sia.tech/the-state-of-sia-december-2023-0973db5b4d94
Oracle cloud infrastructure (2024) Object storage buckets. https://docs.oracle.com/en-us/iaas/Content/Object/Tasks/managingbuckets.htm
Schinnerl, C .(2023).The next generation of renting Sia storage. https://blog.sia.tech/the-next-generation-of-renting-sia-storage-releasing-renterd-v1-0-42ac9ae6d0e8

Is True Database Elasticity Still a Myth?

Wed, 08 Jul 2026 08:51:19 +0000

Is True Database Elasticity Still a Myth? A New Reality Unfolds

Introduction

For years, the promise of truly elastic, “serverless” databases felt like a mirage in the desert of database management. We were told of systems that could scale to zero during idle periods and burst to handle monumental loads, all while paying only for what we used. The reality, however, often fell short: many solutions were merely cleverly packaged auto-scaling groups, saddling organizations with expensive idle costs and the persistent headache of capacity planning. This bred a healthy skepticism among developers and operations teams alike.

Fortunately, that narrative is finally shifting. A new generation of distributed database architectures is emerging, fundamentally redefining what “elasticity” means. These aren’t just incremental improvements to connection pooling or replica sets; they represent a paradigm shift towards truly decoupled compute and storage layers, enabling dynamic resource allocation at an unprecedented, granular level – even per query. This tutorial will explore this architectural evolution and demonstrate conceptually how it delivers on the long-awaited promise of genuine pay-as-you-go database services.

Understanding the Architecture: A Conceptual Walkthrough

The core innovation driving this new wave of elasticity lies in the complete decoupling of compute and storage layers. Traditionally, a database instance (a VM or container) held both its processing power (CPU, RAM) and its local storage. Scaling meant provisioning larger instances or adding more replicas, each with fixed compute and storage capacities, leading to inefficiency.

In the modern elastic database, these functions operate independently:

Storage Layer: This is a highly distributed, shared storage fabric – often an optimized, resilient object store – that handles data persistence, replication, and durability. It scales automatically based on your data volume, and you typically pay only for the storage you consume, without needing to provision disk sizes upfront.
Compute Layer: This is where the magic happens. A pool of processing units is available to execute queries. When a query arrives, the database engine dynamically allocates the necessary compute resources from this pool, fetches data from the shared storage, processes the request, and then releases those resources. This can even happen at the level of individual queries or transactions, rather than whole instances.

Let’s imagine a conceptual configuration for such a service:

# Hypothetical Elastic Database Service Configuration
apiVersion: db.cloudprovider.com/v1
kind: ElasticDatabaseInstance
metadata:
  name: customer-data-prod
spec:
  # Storage Configuration: Self-managing, pay-per-use
  storage:
    type: distributed-shared-storage # Underlying highly-available storage fabric
    replicationStrategy: zonal-redundant
    encryption: KMS-managed
    # No fixed capacity to define; it scales with your data size

  # Compute Configuration: Dynamically allocated, scales to workload
  compute:
    minCapacityUnits: 0.5    # Scales to near zero during idle times (e.g., 0.5 ACUs)
    maxCapacityUnits: 256    # Bursts to a very high limit (e.g., 256 ACUs)
    scalingPolicy:
      targetCPUUtilization: 60%  # Scales up if average CPU exceeds 60%
      targetActiveConnections: 80% # Scales up if connections near limits
      scaleUpCooldownSeconds: 30 # Prevents rapid oscillations
      scaleDownCooldownSeconds: 300 # Ensures stability before de-provisioning
    
    # Connection handling (managed by the service, not your compute)
    connectionPoolMax: 10000
    idleConnectionTimeoutSeconds: 300

  # Monitoring and Observability
  metrics:
    exportTo: prometheus, cloudwatch
    granularity: 1m

In this conceptual layout:

We’re not defining VM sizes or replica counts directly. Instead, we specify minCapacityUnits and maxCapacityUnits. A “Capacity Unit” (ACU, DBU, etc., depending on the vendor) is an abstract measure of compute and memory that the service provides.
minCapacityUnits allows the database to scale down to a very low level (or even zero in some offerings) during periods of no activity, virtually eliminating idle costs.
maxCapacityUnits defines the upper bound for bursting, enabling the database to handle sudden spikes in traffic without manual intervention.
The scalingPolicy details how the service intelligently responds to real-time workload metrics like CPU utilization or active connections, ensuring resources are allocated just-in-time and de-allocated efficiently.

When an application executes a query against customer-data-prod, the elastic database engine analyzes the request, allocates the necessary compute resources from its vast pool, retrieves data from the shared storage, executes the query, and then returns the result. These compute resources are then released, making them available for other queries or allowing the overall compute capacity to scale down if the workload subsides. This pay-per-query or pay-per-second model is the essence of true elasticity.

Conclusion

The journey towards genuine database elasticity has been long, marked by promises and partial fulfillments. However, with the advent of truly decoupled compute and storage architectures, the vision of a database that scales intelligently, granularly, and cost-effectively is finally a reality. These advancements move beyond merely spinning up more nodes; they embody intelligent resource orchestration that dynamically adapts to your workload, whether it’s an intense burst or prolonged idleness.

For organizations, this translates directly into significant cost savings by eradicating wasteful idle capacity and a massive boost to operational sanity by automating the traditionally complex task of database scaling. The era of over-provisioning and costly fixed database instances is genuinely ending. It’s time to embrace these new paradigms and let your cloud bill (and your Ops team’s sanity) finally thank you.

Why can't we just use one storage technology for everything?

Sun, 05 Jul 2026 22:41:00 +0000

Hello, I'm Ganesh. I'm building git-lrc, an AI code reviewer that runs on every commit. It is free, unlimited, and source-available on Github. Star git-lrc on GitHub to help more developers discover the project. Do give it a try and share your feedback for improving the product.

Modern computers use multiple storage and memory technologies because no single medium can simultaneously provide massive capacity, ultra-low latency, high bandwidth, and low cost.

Every level of the memory hierarchy represents a tradeoff between these characteristics.

Why is there a memory hierarchy?

This is because each storage technology has its own advantages and disadvantages. We can't use one storage technology for all the purposes.

The main characteristics to consider are:

Capacity
Latency
Bandwidth
Cost

Each Storage technology is optimized for a specific purpose.

For example:
Imagine you have to travel from one place to another.
You can go with walking, bicycle, car, train, or plane.

Each mode of transport has its own advantages and disadvantages.

Another better example is think of using LLM model.

Depending on task complexity and size of data we can choose the model.

If we mess up with choosing model we will not get the desired output wheather cost will rise, or response will be very low quality.

Memory Hierarchy

Now I have listed down the memory hierarchy From top to bottom.

CPU Registers

This is the fastest storage available inside a processor.

Role:
Stores values currently being operated on by the CPU.

Characteristic	Value
Capacity	Extremely small (typically 32 × 64-bit registers per core)
Latency	~0.3 ns (about one CPU cycle)
Bandwidth	Highest in the system
Cost	Highest cost per bit (16 transistors per bit)

CPU Cache (L1, L2, L3)

A small, ultra-fast memory layer designed to keep frequently used data close to the processor.

Role: Reduces the need to access slower main memory.

Characteristic	Value
Capacity	Small (tens of MB total)
Latency	~7.5 ns (L3 cache)
Bandwidth	Extremely high
Cost	Very expensive (SRAM, 6 transistors per bit)

DRAM (Main Memory)

The working memory used by applications and operating systems.

Role: Holds active programs and data currently being used.

Characteristic	Value
Capacity	Typically 32 GB
Latency	~45 ns
Bandwidth	~48 GB/s
Cost	Higher than storage drives

GPU VRAM

Memory optimized for throughput rather than low latency.
Role: Feeds large amounts of data to thousands of GPU cores simultaneously.

Characteristic	Value
Capacity	~24 GB
Latency	~250 ns
Bandwidth	Extremely high
Cost	Expensive

NVMe SSD

High-speed solid-state storage connected through PCIe.
Role: Fast persistent storage for operating systems, applications, and files.

Characteristic	Value
Capacity	~2 TB
Read Latency	~80 μs
Write Latency	~500 μs
Bandwidth	~5 GB/s
Cost	~7 cents per GB

SATA SSD

An older solid-state storage technology using the SATA interface.

Role: Affordable solid-state storage with lower performance than NVMe.

Characteristic	Value
Capacity	Up to ~4 TB
Latency	~120 μs
Bandwidth	Lower than NVMe
Cost	Similar to NVMe SSDs

Hard Disk Drive (HDD)

Mechanical storage using spinning magnetic platters.
Role: Lowest-cost local storage for large datasets and archives.

Characteristic	Value
Capacity	~8 TB
Latency	~8.3–10 ms
Bandwidth	Very low compared to SSDs
Cost	~1–2 cents per GB

The Fundamental Tradeoff

As we move down the memory hierarchy:

Capacity increases.
Cost per GB decreases.
Latency increases.
Access speed decreases.
Distance from the processor increases.

By leveraging this trade-off, modern computers use a hierarchy of registers, cache, memory, SSDs, HDDs, and cloud storage instead of relying on a single storage technology.

Any feedback or contributors are welcome! It’s online, source-available, and ready for anyone to use.

⭐ Star git-lrc on GitHub

Credits

Here are the sources that inspired me to write an article on this topic.

Why Don’t Computers Just Use One Type of Memory?

windows app secure calculator vault for hide image, video, pdf, text

Mon, 25 May 2026 13:05:07 +0000

secure calculator vault hide and encrypt file. we use AES 256 encryption to encrypt the file. without opening a vault with right password file won't open by other if the third person got the files. also added the built in media viewer so user don't need to leave the app to see this.

supported image extension by media viewer :- png, jpg, jpeg, gif, bmp, webp, svg, tif, tiff, ico

supported video extension by media viewer :- mp4, mkv, mov, webm, avi, mpg, mpeg, ogv

supported text extension by media viewer :- txt, csv, md, log

supported pdf extension by media viewer :- pdf

when user remove the file from the app it automatically decrypt the file.

it's a offline app, Files stay on users device, no background data collection, no ads, no analytics, no user tracking, it support windows 10 and windows 11.

secure calculator vault for media hide

Mon, 25 May 2026 13:03:18 +0000

supported image extension by media viewer :- png, jpg, jpeg, gif, bmp, webp, svg, tif, tiff, ico

supported video extension by media viewer :- mp4, mkv, mov, webm, avi, mpg, mpeg, ogv

supported text extension by media viewer :- txt, csv, md, log

supported pdf extension by media viewer :- pdf

when user remove the file from the app it automatically decrypt the file.

it's a offline app, Files stay on users device, no background data collection, no ads, no analytics, no user tracking, it support windows 10 and windows 11.

Local-First: The Browser as the Vault

Mon, 20 Apr 2026 12:10:00 +0000

Local-First: The Browser as the Vault

“IndexedDB for everything” is a marketing shorthand. Engineers need the three real persistence lanes in this codebase: guest localStorage, authenticated cloud trades, and Zustand prefs-only—plus Firestore IndexedDB cache teardown on logout.

Lane 1 — Guest users: `localPortfolioStore.ts` (localStorage)

Unauthenticated users never hit Firebase for trades. Data lives under namespaced keys:

const STORAGE_KEY_TRADES = 'pocket-portfolio-local-trades';
const STORAGE_KEY_PORTFOLIO = 'pocket-portfolio-local-portfolio';
const STORAGE_KEY_METADATA = 'pocket-portfolio-local-metadata';

saveLocalTrades writes JSON with metadata (tradeCount, dataSize, timestamps). Quota is estimated against a 5MB conservative browser budget (QUOTA_WARNING_THRESHOLD / QUOTA_ERROR_THRESHOLD). When quota goes red, the user gets a hard error — we fail closed rather than silently truncating wealth data.

Engineering takeaway: the “vault” for guests is literally localStorage keys prefixed pocket-portfolio- — not a hosted SQL row.

Lane 2 — Authenticated users: `useTrades` + `TradeService`

When isAuthenticated && user, useTrades loads via:

const userTrades = await TradeService.getTrades(user.uid, true); // forceServerFetch

So authoritative trade history for signed-in users is Firebase-backed (cloud), while the UI working set still behaves local-first: filtering, healed-trade tombstones in localStorage (healedTradeIds), and client-side aggregation before Ask AI.

Do not claim “no server” for auth users — claim no central portfolio DB for LLM inference (Part 1) and minimal product surface area.

Lane 3 — Preferences only: `portfolioStore.ts` + `persist`

zustand/middleware persist uses partialize so we do not dump positions into long-term storage:

partialize: (state) => ({
  chartView: state.chartView,
  timeRange: state.timeRange,
  selectedSectors: state.selectedSectors,
  sectorFilter: state.sectorFilter,
  selectedBenchmark: state.selectedBenchmark,
}),

Chart UX survives reload; sensitive blobs are not persisted here by design.

IndexedDB: where it actually shows up

Firebase Auth + Firestore client SDKs use IndexedDB for offline/cache. On logout, useAuth attempts clearIndexedDbPersistence(db) before terminate(db) — see app/hooks/useAuth.ts. That is cache hygiene, not “portfolio primary store.”

Why not “just use Supabase”?

This is a blast-radius choice: a multi-tenant Postgres of everyone’s ledgers is a different breach story than device-held guest data + user-scoped cloud docs for auth users. We compare architectures, not logos.

Part 5 of Sovereign Engineering.

Read the full Sovereign Intelligence book or try the app.

Where does onetab store data

Mon, 23 Mar 2026 09:56:07 +0000

**Before you dive into this article...**
Check out our vibrant new community at CoderLegion.com!
Share your knowledge, connect with like-minded developers, and grow together.
Click here to join now!

OneTab is one of the well-known browser extensions that collapses all open tabs with one click and saves them as a simple list. From ONeTab, you can save this list as a web page, share it with your friends, or restore them all. But if this is your first time using it, all of these features can feel overwhelming. Don't worry, here is a step-by-step guide on how to use OneTab effectively.

Before you begin

The reason I recommend OneTab over another card manager is the memory usage. I have opened a lot of YouTube tabs that consume more than 1GB of memory, out of my 4GB of RAM. After enabling OneTab, it dropped to almost 44MB, which is a useful drop in memory usage on its own.

I know you already know this, but for those of you who don't, just go to Google and search for OneTab or click here. Then click Add to Chrome. It will automatically be added to Chrome.

You can also see the icon at the top right. To view the quick check or explore the settings panel, right-click on the icon.

It's clean and kind of reminds me of Windows XP. Above it shows the exact number of cards that have been condensed. Just below it shows the date and time of the creation of that specific card. Below you can see options like restore, delete, share as a webpage, etc.

Therefore, all the possible functions that you want to use are right in front of you. Some other options, such as settings, are present at the top right of the page, so there is no intrusion with the main content.

Features
Simply OneTab takes all your cards, condenses them, and puts them into one card, grouping them all. Then you tap and you get a window with a list of pages spread over several tabs.

Basics
This will help you condense all the tabs into one space so that you can expand them all at once by just clicking Restore All. This brings you to the same space before clicking on it. Another quick option is Remove All, which removes all the tabs that you have compressed as soon as you click on them. Although OneTab prompts you to remove tabs first, I suggest you be careful.

Share As Web Page
This is a useful tool when you want to share one group of tabs at a time, as a single accessible web page. By simply clicking on a group, you can send all the cards in that space as a link to anyone. There is also an added barcode that can open the web page while scanning. You, therefore, have the option of a static link and a QCR code.

Delete: I guess this is the function I use the most. It allows me to share all related web pages in one tab. It helps me when writing or reading about a specific topic because I can easily group and tag them.

Group functionality
Grouping all the tabs into one was one thing, but tagging them in groups is just something that helps me be more efficient. I easily name groups and keep them organized.

Get all the basic features separated by groups. But what if you want to add news cards?
As simple as it sounds, you can combine and drag items from one group to another.

Each new tab you close will form a new group that you can rename or add to another group from One Tab.

In addition, you can also lock the group which disables the delete function, which makes it an additional security feature, although I have used it very little.

MinIO Maintenance Mode Explained: Impact on Users & S3 Alternatives

Fri, 27 Feb 2026 21:01:52 +0000

Background: MinIO and the Maintenance Mode announcement

MinIO has long been one of the most popular self-hosted S3-compatible object storage solutions for Kubernetes, especially for logs, backups, and internal object storage in on‑premise and cloud-native environments. Its simplicity, performance, and API compatibility made it a common default choice for backups, artifacts, logs, and internal object storage.

In late 2025, MinIO marked its upstream repository as Maintenance Mode and clarified that the Community Edition would be distributed source-only, without official pre-built binaries or container images. This move triggered renewed discussion across the industry about sustainability, governance, and the risks of relying on a single-vendor-controlled “open core” storage layer.

A detailed industry analysis of this shift, including its broader ecosystem impact, can be found in this InfoQ article

—

What exactly changed?

1. Maintenance Mode

Maintenance Mode means:

No new features
No roadmap-driven improvements
Limited fixes, typically only for critical issues
No active review of community pull requests

As highlighted by InfoQ, this effectively freezes MinIO Community as a stable but stagnant codebase, pushing innovation and evolution exclusively toward the commercial offerings.

2. Source-only distribution

Official binaries and container images are no longer published for the Community Edition. Users must:

Build MinIO from source
Maintain their own container images
Handle signing, scanning, and provenance themselves

This aligns with a broader industry pattern noted by InfoQ: infrastructure projects increasingly shifting operational burden back to users unless they adopt paid tiers.

—

Direct implications for Community users

Security and patching

With no active upstream development:

Vulnerability response times may increase
Users must monitor security advisories independently
Regulated environments may find Community harder to justify

InfoQ emphasizes that this does not make MinIO insecure by default, but it changes the shared-responsibility model significantly.

Operational overhead

Teams now need to:

Pin commits or tags explicitly
Build and test their own releases
Maintain CI pipelines for a core storage dependency

This is a non-trivial cost for what was previously perceived as a “drop‑in” component.

Support and roadmap

The strategic message is clear: active development, roadmap influence, and predictable maintenance live behind the commercial subscription.

—

Impact on OEM and embedded use cases

The InfoQ analysis draws an important distinction between API consumers and technology embedders.

Using MinIO as an external S3 service

If your application simply consumes an S3 endpoint:

The impact is moderate
Migration is largely operational
Application code usually remains unchanged

Embedding or redistributing MinIO

If your product:

Ships MinIO internally
Builds gateways or features on MinIO internals
Depends on MinIO-specific operational tooling

Then the impact is high:

You inherit maintenance and security responsibility
Long-term internal forking becomes likely
Licensing (AGPL) implications must be reassessed carefully

For OEM vendors, this often forces a strategic re-evaluation rather than a tactical upgrade.

—

Forks and community reactions

At the time of writing:

Several community forks focus on preserving the MinIO Console / UI experience
No widely adopted, full replacement fork of the MinIO server exists
Community discussion, as summarized by InfoQ, reflects caution rather than rapid consolidation

The absence of a strong server-side fork suggests that most organizations are choosing migration over replacement-by-fork.

—

Best S3-Compatible Alternatives to MinIO: Ceph RGW, SeaweedFS, Garage

InfoQ highlights that the industry response is not about finding a single “new MinIO”, but about selecting storage systems whose governance and maintenance models better match long-term needs.

Ceph RGW

Best for: Enterprise-grade, highly available environments
Strengths: Mature ecosystem, large community, strong governance
Trade-offs: Operational complexity

SeaweedFS

Best for: Teams seeking simplicity and permissive licensing
Strengths: Apache-2.0 license, active development, integrated S3 API
Trade-offs: Partial S3 compatibility for advanced edge cases

Garage

Best for: Self-hosted and geo-distributed systems
Strengths: Resilience-first design, active open-source development
Trade-offs: AGPL license considerations

Zenko / CloudServer

Best for: Multi-cloud and Scality-aligned architectures
Strengths: Open-source S3 API implementation
Trade-offs: Different architectural assumptions than MinIO

—

Recommended strategies by scenario

If you need to reduce risk immediately

Freeze your current MinIO version
Build, scan, and sign your own images
Define and rehearse a migration path

If you operate Kubernetes on-prem with HA requirements

Ceph RGW is often the most future-proof option

If licensing flexibility is critical

Start evaluation with SeaweedFS

If operational UX matters

Shift toward automation-first workflows
Treat UI forks as secondary tooling, not core infrastructure

—

Conclusion

MinIO’s shift of the Community Edition into Maintenance Mode is less about short-term breakage and more about long-term sustainability and control.

As the InfoQ analysis makes clear, the real risk is not technical incompatibility but governance misalignment. Organizations that treat object storage as critical infrastructure should favor solutions with transparent roadmaps, active communities, and predictable maintenance models.

For many teams, this moment serves as a natural inflection point: either commit to self-maintaining MinIO, move to a commercially supported path, or migrate to a fully open-source alternative designed for the long run.

Want to dive deeper into Kubernetes? This article is part of our , where you’ll find all fundamental and advanced concepts explained step by step.

Frequently Asked Questions

What does Maintenance Mode mean for MinIO Community Edition?

Maintenance Mode for MinIO Community Edition means the upstream codebase is effectively frozen. There will be no new features, only critical bug fixes, and community pull requests will not be actively reviewed. Furthermore, official pre-built binaries and container images are no longer provided; users must build from source.

Is MinIO Community Edition still safe to use?

The code itself isn’t inherently insecure, but the shared-responsibility model changes. Security patching for non-critical issues will be slower or non-existent. For production, especially in regulated environments, you must now actively monitor advisories and maintain your own built and scanned images, which increases operational risk.

What is the best open-source alternative to MinIO for Kubernetes?

The best alternative depends on your needs. For enterprise-grade, high-availability setups, Ceph RGW is the most robust choice. For simplicity and Apache 2.0 licensing, SeaweedFS is excellent. For geo-distributed, resilience-first designs, evaluate Garage. There is no direct drop-in replacement; each requires evaluation.

Should I fork MinIO or migrate to another solution?

For most organizations, migration is preferable to forking. Maintaining a full fork of a complex storage server involves significant long-term commitment to security, bug fixes, and potential feature backporting. The industry trend, as noted, is toward migration to systems with active upstream development and clear governance.

How does this affect products that embed MinIO (OEM use)?

The impact on OEMs is high. You inherit full maintenance and security responsibility. Long-term internal forking becomes likely, and the AGPL licensing implications must be carefully reassessed. This often forces a strategic re-evaluation of your embedded storage layer rather than a simple tactical update.

MinIO Maintenance Mode Explained: Impact on Community Users, OEMs, and S3 Alternatives

Sat, 14 Feb 2026 03:25:32 +0000

Background: MinIO and the Maintenance Mode announcement

MinIO has long been one of the most popular self-hosted S3-compatible object storage solutions, especially in Kubernetes and on‑premise environments. Its simplicity, performance, and API compatibility made it a common default choice for backups, artifacts, logs, and internal object storage.

A detailed industry analysis of this shift, including its broader ecosystem impact, can be found in this InfoQ article

—

What exactly changed?

1. Maintenance Mode

Maintenance Mode means:

No new features
No roadmap-driven improvements
Limited fixes, typically only for critical issues
No active review of community pull requests

As highlighted by InfoQ, this effectively freezes MinIO Community as a stable but stagnant codebase, pushing innovation and evolution exclusively toward the commercial offerings.

2. Source-only distribution

Official binaries and container images are no longer published for the Community Edition. Users must:

Build MinIO from source
Maintain their own container images
Handle signing, scanning, and provenance themselves

This aligns with a broader industry pattern noted by InfoQ: infrastructure projects increasingly shifting operational burden back to users unless they adopt paid tiers.

—

Direct implications for Community users

Security and patching

With no active upstream development:

Vulnerability response times may increase
Users must monitor security advisories independently
Regulated environments may find Community harder to justify

InfoQ emphasizes that this does not make MinIO insecure by default, but it changes the shared-responsibility model significantly.

Operational overhead

Teams now need to:

Pin commits or tags explicitly
Build and test their own releases
Maintain CI pipelines for a core storage dependency

This is a non-trivial cost for what was previously perceived as a “drop‑in” component.

Support and roadmap

The strategic message is clear: active development, roadmap influence, and predictable maintenance live behind the commercial subscription.

—

Impact on OEM and embedded use cases

The InfoQ analysis draws an important distinction between API consumers and technology embedders.

Using MinIO as an external S3 service

If your application simply consumes an S3 endpoint:

The impact is moderate
Migration is largely operational
Application code usually remains unchanged

Embedding or redistributing MinIO

If your product:

Ships MinIO internally
Builds gateways or features on MinIO internals
Depends on MinIO-specific operational tooling

Then the impact is high:

You inherit maintenance and security responsibility
Long-term internal forking becomes likely
Licensing (AGPL) implications must be reassessed carefully

For OEM vendors, this often forces a strategic re-evaluation rather than a tactical upgrade.

—

Forks and community reactions

At the time of writing:

Several community forks focus on preserving the MinIO Console / UI experience
No widely adopted, full replacement fork of the MinIO server exists
Community discussion, as summarized by InfoQ, reflects caution rather than rapid consolidation

The absence of a strong server-side fork suggests that most organizations are choosing migration over replacement-by-fork.

—

Fully open-source alternatives to MinIO

InfoQ highlights that the industry response is not about finding a single “new MinIO”, but about selecting storage systems whose governance and maintenance models better match long-term needs.

Ceph RGW

Best for: Enterprise-grade, highly available environments
Strengths: Mature ecosystem, large community, strong governance
Trade-offs: Operational complexity

SeaweedFS

Garage

Best for: Self-hosted and geo-distributed systems
Strengths: Resilience-first design, active open-source development
Trade-offs: AGPL license considerations

Zenko / CloudServer

Best for: Multi-cloud and Scality-aligned architectures
Strengths: Open-source S3 API implementation
Trade-offs: Different architectural assumptions than MinIO

—

Recommended strategies by scenario

If you need to reduce risk immediately

Freeze your current MinIO version
Build, scan, and sign your own images
Define and rehearse a migration path

If you operate Kubernetes on-prem with HA requirements

Ceph RGW is often the most future-proof option

If licensing flexibility is critical

Start evaluation with SeaweedFS

If operational UX matters

Shift toward automation-first workflows
Treat UI forks as secondary tooling, not core infrastructure

—

Conclusion

MinIO’s shift of the Community Edition into Maintenance Mode is less about short-term breakage and more about long-term sustainability and control.

Want to dive deeper into Kubernetes? This article is part of our comprehensive Kubernetes Architecture Patterns guide, where you’ll find all fundamental and advanced concepts explained step by step.

MongoDB: A Beginner's Guide to NoSQL Databases

Sun, 02 Feb 2025 09:56:37 +0000

What is MongoDB?

MongoDB is a NoSQL, document-based database that stores data in a JSON-like format called BSON (Binary JSON). Unlike SQL databases, MongoDB does not require a fixed schema. This flexibility makes it great for applications that need to scale quickly and manage different types of data.

Example:

Imagine a social media app storing user information. Each user may have different attributes: some may have phone numbers, others might not. MongoDB allows you to store this data without needing to define a rigid structure, unlike traditional SQL databases.

What MongoDB is Not

MongoDB is not a relational database.

While SQL databases work best for applications that require strict relationships between data (like financial systems or traditional enterprise applications), MongoDB is best for handling unstructured data or applications that require quick scalability, like real-time analytics, content management systems, and IoT platforms.

Why You Should Learn MongoDB

As the demand for modern, data-driven applications continues to grow, MongoDB is becoming more relevant. Here's why learning MongoDB in 2025 is a good idea:

Growing Demand: More companies are adopting NoSQL databases for their flexibility and scalability.
Ease of Use: MongoDB's document-based structure is easier to work with than SQL's table-based structure, making it ideal for beginners.
Big Data and Cloud-Friendly: MongoDB is widely used for managing big data and working in cloud environments.

MongoDB vs SQL

One of the most common comparisons is between MongoDB and traditional SQL databases.

- Schema: SQL requires a fixed schema (tables, rows, columns), while MongoDB's schema-less design allows you to store different types of data without predefined structures.

- Scaling: MongoDB is built to scale horizontally (across multiple servers), while SQL databases often scale vertically (increasing server power).

- Data Storage: SQL uses tables to store data, while MongoDB stores data in collections of documents, which are more flexible.

Advantages of Using MongoDB

Scalability: MongoDB can handle large amounts of data, scaling easily as your application grows.
Flexibility: It allows for storing various data types, from simple records to complex documents with nested arrays and objects.
High Performance: MongoDB offers fast data retrieval due to its document-based structure.
Real-time Analytics: MongoDB is ideal for applications that require real-time processing, like analytics platforms.

MongoDB Drawbacks

While MongoDB has many advantages, it's important to note a few drawbacks:

Lack of Complex Transactions: While MongoDB supports basic transactions, it doesn't handle complex multi-table transactions as efficiently as SQL databases.
Consistency: In certain use cases, MongoDB might sacrifice strict data consistency (ACID properties) for performance and scalability. This could be a concern for systems that require precise consistency, like banking systems.

When to Use MongoDB

You should consider using MongoDB when:

You are building a project that requires scalability and flexibility, such as social networks, content management systems, or real-time analytics platforms.
Your application deals with unstructured or semi-structured data (e.g., logs, user-generated content, etc.).
You need fast development cycles and agile methodologies where schema design might change often.

When Not to Use MongoDB

MongoDB is not ideal when:

Your project requires complex transactions (e.g., banking applications or systems requiring multi-step business logic).
Your data needs to follow strict relationships and constraints (e.g., inventory systems, financial applications, or CRM systems).
Consistency is more important than availability or partition tolerance (known as the CAP theorem).

Benefits of MongoDB:

Schema Flexibility: Ideal for applications that handle varying types of data.
Horizontal Scalability: You can scale your app seamlessly with sharding.
High Availability: MongoDB supports replication for fault tolerance.
Faster Development: You can iterate faster with MongoDB's flexible data structure.

Despite the benefits, MongoDB may not be suitable for all use cases.

Learning Curve: Although MongoDB is beginner-friendly, getting familiar with its advanced features (like sharding and replication) can take time.
Data Integrity: MongoDB does not enforce data integrity as strictly as relational databases, so it's important to plan for handling data consistency issues in your application.

Conclusion

MongoDB is an excellent choice for modern applications that need scalability, flexibility, and fast development. While it's not suitable for all use cases, especially those requiring complex transactions or rigid data structures, it is a powerful tool for developers working on dynamic applications. By understanding the strengths and weaknesses of MongoDB, you can make an informed decision about whether it's the right tool for your project.

Have you worked with MongoDB before? What was your experience? Share your thoughts in the comments below, or feel free to ask questions. For more beginner tutorials, check out my related articles!

Glossary

NoSQL: A type of database designed to handle unstructured or semi-structured data.
BSON: A binary format of JSON used by MongoDB for storing documents.
Sharding: A method of distributing data across multiple servers to ensure scalability.
Replication: The process of copying data across multiple servers to ensure high availability.

Coder Legion - Recent posts tagged storage

The Decentralized Storage Revolution: Exploring SIA's Tech Exploring S3 gateway with Sia's renterd.

Reference

Is True Database Elasticity Still a Myth?

Is True Database Elasticity Still a Myth? A New Reality Unfolds

Introduction

Understanding the Architecture: A Conceptual Walkthrough

Conclusion

Why can't we just use one storage technology for everything?

Why is there a memory hierarchy?

Memory Hierarchy

CPU Registers

CPU Cache (L1, L2, L3)

DRAM (Main Memory)

GPU VRAM

NVMe SSD

SATA SSD

Hard Disk Drive (HDD)

The Fundamental Tradeoff

Credits

windows app secure calculator vault for hide image, video, pdf, text

secure calculator vault for media hide

Local-First: The Browser as the Vault

Local-First: The Browser as the Vault

Lane 1 — Guest users: localPortfolioStore.ts (localStorage)

Lane 2 — Authenticated users: useTrades + TradeService

Lane 3 — Preferences only: portfolioStore.ts + persist

IndexedDB: where it actually shows up

Why not “just use Supabase”?

Where does onetab store data

MinIO Maintenance Mode Explained: Impact on Users & S3 Alternatives

Background: MinIO and the Maintenance Mode announcement

What exactly changed?

1. Maintenance Mode

2. Source-only distribution

Direct implications for Community users

Security and patching

Operational overhead

Support and roadmap

Impact on OEM and embedded use cases

Using MinIO as an external S3 service

Embedding or redistributing MinIO

Forks and community reactions

Best S3-Compatible Alternatives to MinIO: Ceph RGW, SeaweedFS, Garage

Ceph RGW

SeaweedFS

Garage

Zenko / CloudServer

Recommended strategies by scenario

If you need to reduce risk immediately

If you operate Kubernetes on-prem with HA requirements

If licensing flexibility is critical

If operational UX matters

Conclusion

Frequently Asked Questions

What does Maintenance Mode mean for MinIO Community Edition?

Is MinIO Community Edition still safe to use?

What is the best open-source alternative to MinIO for Kubernetes?

Should I fork MinIO or migrate to another solution?

How does this affect products that embed MinIO (OEM use)?

Related posts

Related articles:

MinIO Maintenance Mode Explained: Impact on Community Users, OEMs, and S3 Alternatives

Background: MinIO and the Maintenance Mode announcement

What exactly changed?

1. Maintenance Mode

2. Source-only distribution

Direct implications for Community users

Security and patching

Operational overhead

Support and roadmap

Impact on OEM and embedded use cases

Using MinIO as an external S3 service

Embedding or redistributing MinIO

Forks and community reactions

Fully open-source alternatives to MinIO

Ceph RGW

SeaweedFS

Garage

Zenko / CloudServer

Lane 1 — Guest users: `localPortfolioStore.ts` (localStorage)

Lane 2 — Authenticated users: `useTrades` + `TradeService`

Lane 3 — Preferences only: `portfolioStore.ts` + `persist`