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SAP BTP Expert Series Southeast Asia: Make Your Business Unstoppable
SAP BTP Expert Series Southeast Asia:
Make Your Business UnstoppableDiscover how the SAP Business Technology Platform (BTP) and our Partners can accelerate your journey to SAP S/4HANA Cloud, driving faster, continuous innovation by optimizing and seamlessly connecting your end-to-end processes.
Dear MD Abul Khayer,We’re excited to invite you to the SAP BTP Expert Series Southeast Asia 2025 - a dynamic 7-part webinar series designed to accelerate your transformation journey with SAP Business Technology Platform (BTP).
Throughout the series, you’ll gain valuable insights through:
- Bite-Sized Insights – Short, focused sessions that simplify complex topics into practical, actionable takeaways.
- Strategic Focus – Explore business-ready, trusted, and user-friendly AI capabilities deeply embedded in SAP BTP technologies.
- Expert Guidance – Connect directly with SAP and Partner professionals who bring deep expertise in the SAP Cloud Journey.
- Why Attend?
- Empower your business with strategic, hands-on insights and unlock the full potential of SAP BTP to drive innovation, agility, and continuous growth.
Don’t miss out on this opportunity to future-proof your business.
We look forward to your participation!Best regards,
SAPJoin our webinar 
Part 1: Reduce Technical Debt, Upgrade faster, and Innovate with Agility using SAP Clean Core Framework 
Part 2: Transform Data Migration into a Competitive Advantage with Syniti ADMM 
Part 3: Navigating S/4HANA Transformation : Automating Content & Compliance with SAP & OpenText 
Part 4: Drive SAP S/4HANA success with Tricentis for comprehensive, accelerated Quality Engineering 
Part 5 - Automate, optimize, and innovate faster together with SAP and UiPath 
Part 6 - Modernizing your PI/PO landscape for greater efficiency 
Part 7: Ensure Data Integrity and Governance with SimpleMDG for Stronger Business Outcomes 
Watch in on Demand After 9 May 2023
On-DemandBest regards,
SAP
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by "SAP South East Asia" <sap@mailsap.com> - 08:02 - 1 May 2025 -
Synchronous vs Asynchronous Communication: When to Use What?
Synchronous vs Asynchronous Communication: When to Use What?
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A system's usefulness depends heavily on its ability to communicate with other systems.
That’s true whether it’s a pair of microservices exchanging user data, a mobile app fetching catalog details, or a distributed pipeline pushing events through a queue. At some point, every system has to make a call: Should this interaction happen synchronously or asynchronously?
That question surfaces everywhere: sometimes explicitly in design documents, sometimes buried in architectural decisions that later appear as latency issues, cascading failures, or observability blind spots. It affects how APIs are designed, how systems scale, and how gracefully they degrade when things break.
Synchronous communication feels familiar. One service calls another, waits for a response, and moves on. It’s clean, predictable, and easy to trace. However, when the service being called slows down or fails, then everything that depends on it also gets impacted.
Asynchronous communication decouples these dependencies. A message is published, a job is queued, or an event is fired, and the sender moves on. It trades immediacy for flexibility. The system becomes more elastic, but harder to debug, reason about, and control.
Neither approach is objectively better. They serve different needs, and choosing between them (or deciding how to combine them) is a matter of understanding different trade-offs:
Latency versus throughput
Simplicity versus resilience
Real-time response versus eventual progress
In this article, we’ll take a detailed look at synchronous and asynchronous communication, along with their trade-offs. We will also explore some popular communication protocols that make synchronous or asynchronous communication possible.
Understanding the Basics...
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by "ByteByteGo" <bytebytego@substack.com> - 11:36 - 1 May 2025 -
New Relic University Observability Workshop Series
New Relic
We're excited to offer a series of 90 minute online workshops designed to enhance your skills and get you ready for securing the New Relic Certification of your choice. Whether you’re a seasoned professional or just starting your observability journey, our courses are designed to propel your career forward with New Relic and observability.
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Register for the full series below or individual workshops, and click on the links above to explore each session and secure your spot today!
Register now
by "New Relic University" <emeamarketing@newrelic.com> - 05:02 - 1 May 2025 -
The benefits of better mental health—for everyone
On McKinsey Perspectives
by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 11:05 - 30 Apr 2025 -
AI Is Moving Faster Than Your ERP – Are You Ready?
AI Is Moving Faster Than Your ERP – Are You Ready?
Hi MD Abul,
We’re seeing a pattern across organizations of all sizes: leadership teams are excited about AI, but unclear on what it actually means for their business.
Some are trying to apply AI too broadly, too fast. Others are waiting for a perfect plan that never arrives. Either way, the result is the same: a lot of talk, but little progress.
Here’s our take:
An effective AI strategy doesn’t start with tech. It starts with business value. The organizations getting the most out of AI are the ones using it to solve real problems in operations, customer experience, or decision-making, not just chasing hype.If you’re still working through what AI looks like for your transformation, that’s normal. But the time to shape your roadmap is now, before the pressure to act overrides the plan.
This is a big focus at Digital Stratosphere 2025 this August in Denver. The theme?
Mission AI-Possible - Navigating the Future of Digital EvolutionReserve your spot now:
https://www.thirdstage-consulting.com/stratosphere-2025Let us know if you have questions—we’d love to see you there.
Best regards,
Eric Kimberling
by "Eric Kimberling" <eric.kimberling@thirdstage-consulting.com> - 06:03 - 30 Apr 2025 -
SCIC - lifting and conveying chain solutions
Dear info,
Hope this finds you well!
We major in round steel link chain & accessories manufacture and supply!
Per attached please find our catalog for your information (or visit: www.scic-chain.com).
SCIC as a 30+ year manufacturer focus on high quality chains:
- G80 & G100 lifting chains & slings per EN 818-2/-4/-7 and NACM;
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- SCIC total quality control (TQC) system as ISO9001 certified;
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We look forward to the opportunity of working with your company and supplying to your expectations.
Thanks and kindest regards,
Tony Shum
Mp: +86 131 226 00975 (WhatsApp)
Tel: +86 21 313 00975
WeChat: scic-cn
Shanghai Chigong Industrial Co., Ltd.
C-888, Huanhuxi 2 Road, Lin-Gang Special Area,
China (Shanghai) Pilot Free Trade Zone, Shanghai, China
www.scic-chain.com
by "Anna" <Anna@elight-tech.com> - 01:04 - 30 Apr 2025 -
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by "SAP Sapphire" <sap@mailsap.com> - 05:40 - 30 Apr 2025 -
Et si on trouvait une meilleure solution ?
Bonjour,
Vous avez sûrement déjà une solution pour la musique chez Achilles Coaching Sport Santé, mais est-ce vraiment la plus efficace ?
Beaucoup de commerces passent à une musique sans pub, sans redevances cachées, et adaptée à leur ambiance.
Ça pourrait être intéressant pour vous aussi ?
Dites-moi ce que vous en pensez, je serais ravi(e) d’en discuter ! 😊
Romain
by "Romain Rigaud" <romain.rigaud@license-jamendo.fr> - 05:29 - 30 Apr 2025 -
Your Dream Day at the Races - Made Affordable
Hello,
We believe that premium hospitality should be accessible for everyone. That’s why Corporate Race Day offers flexible payment options to suit every budget:
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by "Josh - Corporate Race Day" <joinus@corporateraceday.com> - 03:45 - 30 Apr 2025 -
Navigating the energy transition’s physical challenges
On McKinsey Perspectives
Brought to you by Alex Panas, global leader of industries, & Axel Karlsson, global leader of functional practices and growth platforms
Welcome to the latest edition of Only McKinsey Perspectives. We hope you find our insights useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
—Alex and Axel
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An immense physical change. At the heart of the energy transition lies an ongoing challenge. Shifting the world from high-emission technologies that rely on fossil fuels to low-emission options requires a massive physical transformation, McKinsey Senior Partners Chris Bradley and Humayun Tai and their coauthors share. Today’s complex system of energy production and consumption is connected to billions of parts that need to be overhauled—and all within a few decades.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 01:48 - 30 Apr 2025 -
High-quality soft bait packaging solutions for your brand
Dear info,
I hope you are well after receiving this message.
My name is Fannie and I am an employee of TOP PACK, a trusted packaging manufacturer specializing in high-quality composite bags and clamshell packaging for soft fishing baits. Our customers include well-known brands such as Mustad, Googan, Creme Lure and Bass Pro Shops, and we are honored to provide the same excellent service for your packaging needs.
Our fishing bait packaging has the following advantages:
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With more than 15 years of experience and certifications such as BRC and ISO 9001, we have the ability to meet your high standards. The high efficiency and cost-effectiveness of our factory enable us to offer competitive prices and flexible MOQs to suit brands of all sizes.
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by "Nolvis Bch" <nolvisbch@gmail.com> - 10:46 - 29 Apr 2025 -
Secure your Spot! Register now for the Agentforce World Tour Broadcast
Secure your Spot! Register now for the Agentforce World Tour Broadcast
29 May 2025
9:00 a.m. BKT/ICT | 10:00 a.m. SGTRegister now Agentforce World Tour Broadcast
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We can’t wait to welcome you!Register now Captions will be available during the broadcast for Traditional Chinese, Thai, Vietnamese, and Bahasa Indonesia. Your unique viewing link for the broadcast event will be sent to you in a confirmation email upon registering.
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by "Salesforce Events" <aseanevents@salesforce.com> - 10:02 - 29 Apr 2025 -
Manufacturer of Bamboo products HC.XIAMEN
Dear info,
We are a direct vendor and focus on export barrel and wood display rack.
Glad to know you also serve in this industry, we are good at manufacturing permanent display racks, retail store fixtures, and signage, we have our own factory with advanced equipments of barrel, wood, bamboo and metal products, and have a good advantage in the prices and reference.
Could you please send us a project to have a try?
Best regards,
by "jack" <jack@ivtem.com> - 06:39 - 29 Apr 2025 -
Nonwoven Products and Rolls —— Hangzhou Hongrun Nonwovens Co., Ltd
Dear info ,
I hope this message finds you well.
My name is Boehmer Franchesca，a leading manufacturer specializing in spunlaced non-woven fabric rolls and products, including wax strips, wax roll, cleaning rags, disposable sheets, disposable towels, and disposable masks, wet wipes and, so on!85% of our products are exported to European market, followed by North America, Western Europe, Japan, Korea, etc.
About Depilation wax paper, our company accounts for 2/3 of the foreign market. For example, Sassoon in the United States purchases wax paper from our company.
We pride ourselves on our ability to customize our products to meet the specific requirements of our clients.
We are eager to explore potential partnerships with your esteemed company. We believe our products can add significant value to your offerings and help you meet the demands of your market. We would be delighted to provide you with samples for evaluation and discuss any specific needs you may have.
Please let us know a convenient time for you to have a discussion, or feel free to reach out if you have any questions. We look forward to the opportunity to collaborate and contribute to your success.
Thank you for considering as a potential partner. We hope to hear from you soon.
Best regards,
by "Boehmer Franchesca" <franchescaboehmer@gmail.com> - 12:51 - 29 Apr 2025 -
How Meta Built Threads to Support 100 Million Signups in 5 Days
How Meta Built Threads to Support 100 Million Signups in 5 Days
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Disclaimer: The details in this post have been derived from the articles written by the Meta engineering team. All credit for the technical details goes to the Meta/Threads Engineering Team. The links to the original articles and videos are present in the references section at the end of the post. We’ve attempted to analyze the details and provide our input about them. If you find any inaccuracies or omissions, please leave a comment, and we will do our best to fix them.
Threads, Meta’s newest social platform, launched on July 5, 2023, as a real-time, public conversation space.
Built in under five months by a small engineering team, the product received immediate momentum. Infrastructure teams had to respond immediately to the incredible demand.
When a new app hits 100 million signups in under a week, the instinct is to assume someone built a miracle backend overnight. That’s not what happened with Threads. There was no time to build new systems or bespoke scaling plans. The only option was to trust the machinery already in place.
And that machinery worked quite smoothly. As millions signed up in 5 days, the backend systems held on, and everything from the user’s perspective worked as intended.
Threads didn’t scale because it was lucky. It scaled because it inherited Meta’s hardened infrastructure: platforms shaped by a decade of lessons from Facebook, Instagram, and WhatsApp.
This article explores two of those platforms that played a key role in the successful launch of Threads:
ZippyDB, the distributed key-value store powering state and search.
Async, the serverless compute engine that offloads billions of background tasks.
Neither of these systems was built for Threads. But Threads wouldn’t have worked without them.
ZippyDB was already managing billions of reads and writes daily across distributed regions. Also, Async had been processing trillions of background jobs across more than 100,000 servers, quietly powering everything from feed generation to follow suggestions.
ZippyDB: Key-Value at Hyperscale
ZippyDB is Meta’s internal, distributed key-value store designed to offer strong consistency, high availability, and geographical resilience at massive scale.
At its core, it builds on RocksDB for storage, extends replication with Meta’s Data Shuttle (a Multi-Paxos-based protocol), and manages placement and failover through a system called Shard Manager.
Unlike purpose-built datastores tailored to single products, ZippyDB is a multi-tenant platform. Dozens of use cases (from metadata services to product feature state) share the same infrastructure. This design ensures higher hardware utilization, centralized observability, and predictable isolation across workloads.
The Architecture of ZippyDB
ZippyDB doesn’t treat deployment as a monolith. It’s split into deployment tiers: logical groups of compute and storage resources distributed across geographic regions.
Each tier serves one or more use cases and provides fault isolation, capacity management, and replication boundaries. The most commonly used is the wildcard tier, which acts as a multi-tenant default, balancing hardware utilization with operational simplicity. Dedicated tiers exist for use cases with strict isolation or latency constraints.
Within each tier, data is broken into shards, the fundamental unit of distribution and replication. Each shard is independently managed and:
Synchronously replicated across a quorum of Paxos nodes for durability and consistency. This guarantees that writes survive regional failures and meet strong consistency requirements.
Asynchronously replicated to follower replicas, which are often co-located with high-read traffic regions. These replicas serve low-latency reads with relaxed consistency, enabling fast access without sacrificing global durability.
This hybrid replication model (strong quorum-based writes paired with regional read optimization) gives ZippyDB flexibility across a spectrum of workloads.
See the diagram below that shows the concept of region-based replication supported by ZippyDB.
To push scalability even further, ZippyDB introduces a layer of logical partitioning beneath shards: μshards (micro-shards). These are small, related key ranges that provide finer-grained control over data locality and mobility.
Applications don’t deal directly with physical shards. Instead, they write to μshards, which ZippyDB dynamically maps to underlying storage based on access patterns and load balancing requirements.
ZippyDB supports two primary strategies for managing μshard-to-shard mapping:
Compact Mapping: Best for workloads with relatively static data distribution. Mappings change only when shards grow too large or too hot. This model prioritizes stability over agility and is common in systems with predictable access patterns.
Akkio Mapping: Designed for dynamic workloads. A system called Akkio continuously monitors access patterns and remaps μshards to optimize latency and load. This is particularly valuable for global products where user demand shifts across regions throughout the day. Akkio reduces data duplication while improving locality, making it ideal for scenarios like feed personalization, metadata-heavy workloads, or dynamic keyspaces.
In ZippyDB, the Shard Manager acts as the external controller for leadership and failover. It doesn’t participate in the data path but plays a critical role in keeping the system coordinated.
The Shard Manager assigns a Primary replica to each shard and defines an epoch: a versioned leadership lease. The epoch ensures only one node has write authority at any given time. When the Primary changes (for example, due to failure), Shard Manager increments the epoch and assigns a new leader. The Primary sends regular heartbeats to the Shard Manager. If the heartbeats stop, the Shard Manager considers the Primary unhealthy and triggers a leader election by promoting a new node and bumping the epoch.
See the diagram below that shows the role of the Shard Manager:
Consistency and Durability in ZippyDB
In distributed systems, consistency is rarely black-and-white. ZippyDB embraces this by giving clients per-request control over consistency and durability levels, allowing teams to tune system behavior based on workload characteristics.
1 - Strong Consistency
Strong consistency in ZippyDB ensures that reads always reflect the latest acknowledged writes, regardless of where the read or write originated. To achieve this, ZippyDB routes these reads to the primary replica, which holds the current Paxos lease for the shard. The lease ensures that only one primary exists at any time, and only it can serve linearizable reads.
If the lease state is unclear (for example, during a leadership change), the read may fall back to a quorum check to avoid split-brain scenarios. This adds some latency, but maintains correctness.
2 - Bounded Staleness (Eventual Consistency)
Eventual consistency in ZippyDB isn’t the loose promise it implies in other systems. Here, it means bounded staleness: a read may be slightly behind the latest write, but it will never serve stale data beyond a defined threshold.
Follower replicas (often located closer to users) serve these reads. ZippyDB uses heartbeats to monitor follower lag, and only serves reads from replicas that are within an acceptable lag window. This enables fast, region-local reads without compromising on the order of operations.
3 - Read-Your-Writes Consistency
For clients that need causal guarantees, ZippyDB supports a read-your-writes model.
After a write, the server returns a version number (based on Paxos sequence ordering). The client caches this version and attaches it to subsequent reads. ZippyDB then ensures that reads reflect data at or after that version.
This model works well for session-bound workloads, like profile updates followed by an immediate refresh.
4 - Fast-Ack Write Mode
In scenarios where write latency matters more than durability, ZippyDB offers a fast-acknowledgment write mode. Writes are acknowledged as soon as they are enqueued on the primary for replication, not after they’re fully persisted in the quorum.
This boosts throughput and responsiveness, but comes with trade-offs:
Lower durability (data could be lost if the primary crashes before replication).
Weaker consistency (readers may not see the write until replication completes).
This mode fits well in systems that can tolerate occasional loss or use an idempotent retry.
Transactions and Conditional Writes
ZippyDB supports transactional semantics for applications that need atomic read-modify-write operations across multiple keys. Unlike systems that offer tunable isolation levels, ZippyDB keeps things simple and safe: all transactions are serializable by default.
Transactions
ZippyDB implements transactions using optimistic concurrency control:
Clients read a database snapshot (usually from a follower) and assemble a write set.
They send both read and write sets, along with the snapshot version, to the primary.
The primary checks for conflicts, whether any other transaction has modified the same keys since the snapshot.
If there are no conflicts, the transaction commits and is replicated via Paxos.
If a conflict is detected, the transaction is rejected, and the client retries. This avoids lock contention but works best when write conflicts are rare.
ZippyDB maintains recent write history to validate transaction eligibility. To keep overhead low, it prunes older states periodically. Transactions spanning epochs (i.e., across primary failovers) are automatically rejected, which simplifies correctness guarantees at the cost of some availability during leader changes.
Conditional Writes
For simpler use cases, ZippyDB exposes a conditional write API that maps internally to a server-side transaction. This API allows operations like:
“Set this key only if it doesn’t exist.”
“Update this value only if it matches X.”
“Delete this key only if it’s present.”
These operations avoid the need for client-side reads and round-trips. Internally, ZippyDB evaluates the precondition, checks for conflicts, and commits the write as a transaction if it passes.
This approach simplifies client code and improves performance in cases where logic depends on the current key's presence or state.
Why was ZippyDB critical To Threads?
Threads didn’t have months to build a custom data infrastructure. It needed to read and write at scale from day one. ZippyDB handled several core responsibilities, such as:
Counters: Like counts, follower tallies, and other rapidly changing metrics.
Feed ranking state: Persisted signals to sort and filter what shows up in a user's home feed.
Search state: Underlying indices that powered real-time discovery.
What made ZippyDB valuable wasn’t just performance but adaptability. As a multi-tenant system, it supported fast onboarding of new services. Teams didn’t have to provision custom shards or replicate schema setups. They configured what they needed and got the benefit of global distribution, consistency guarantees, and monitoring from day one.
At launch, Threads was expected to grow. But few predicted the velocity: 100 million users in under a week. That kind of growth doesn’t allow for manual shard planning or last-minute migrations.
ZippyDB’s resharding protocol turned a potential bottleneck into a non-event. Its clients map data into logical shards, which are dynamically routed to physical machines. When load increases, the system can:
Provision new physical shards.
Reassign logical-to-physical mappings live, without downtime.
Migrate data using background workers that ensure consistency through atomic handoffs.
No changes are required in the application code. The system handles remapping and movement transparently. Automation tools orchestrate these transitions, enabling horizontal scale-out at the moment it's needed, not hours or days later.
This approach allowed Threads to start small, conserve resources during early development, and scale adaptively as usage exploded, without risking outages or degraded performance.
During Threads’ launch window, the platform absorbed thousands of machines in a matter of hours. Multi-tenancy played a key role here. Slack capacity from lower-usage keyspaces was reallocated, and isolation boundaries ensured that Threads could scale up without starving other workloads.
Async - Serverless at Meta Scale
Async is Meta’s internal serverless compute platform, formally known as XFaaS (eXtensible Function-as-a-Service).
At peak, Async handles trillions of function calls per day across more than 100,000 servers. It supports multiple languages such as HackLang, Python, Haskell, and Erlang.
What sets Async apart is the fact that it abstracts away everything between writing a function and running it on a global scale. There is no need for service provisioning. Drop code into Async, and it inherits Meta-grade scaling, execution guarantees, and disaster resilience.
Async’s Role in Threads
When Threads launched, one of the most critical features wasn’t visible in the UI. It was the ability to replicate a user’s Instagram follow graph with a single tap. Behind that one action sat millions of function calls: each new Threads user potentially following hundreds or thousands of accounts in bulk.
Doing that synchronously would have been a non-starter. Blocking the UI on graph replication would have led to timeouts, poor responsiveness, and frustrated users. Instead, Threads offloaded that work to Async.
Async queued those jobs, spread them across the fleet, and executed them in a controlled manner. That same pattern repeated every time a celebrity joined Threads—millions of users received follow recommendations and notifications, all piped through Async without spiking database load or flooding services downstream.
How Async Handled the Surge
Async didn’t need to be tuned for Threads. It scaled the way it always does.
Several features were key to the success of Threads:
Queueing deferred less-urgent jobs to prevent contention with real-time tasks.
Batching combined many lightweight jobs into fewer, heavier ones, reducing overhead on dispatchers and improving cache efficiency.
Capacity-aware scheduling throttled job execution when downstream systems (like ZippyDB or the social graph service) showed signs of saturation.
This wasn’t reactive tuning. It was a proactive adaptation. Async observed system load and adjusted flow rates automatically. Threads engineers didn’t need to page anyone or reconfigure services. Async matched its execution rate to what the ecosystem could handle.
Developer Experience
One of the most powerful aspects of Async is that the Threads engineers didn’t need to think about scale. Once business logic was written and onboarded into Async, the platform handled the rest:
Delivery windows: Jobs could specify execution timing, allowing deferment or prioritization.
Retries: Transient failures were retried with backoff, transparently.
Auto-throttling: Job rates were adjusted dynamically based on system health.
Multi-tenancy isolation: Surges in one product didn’t impact another.
These guarantees allowed engineers to focus on product behavior, not operational limits. Async delivered a layer of predictable elasticity, absorbing traffic spikes that would have crippled a less mature system.
Conclusion
The Threads launch was like a stress test for Meta’s infrastructure. And the results spoke for themselves. A hundred million users joined in less than a week. But there were no major outages.
That kind of scale doesn’t happen by chance.
ZippyDB and Async weren’t built with Threads in mind. But Threads only succeeded because those systems were already in place, hardened by a decade of serving billions of users across Meta’s core apps. They delivered consistency, durability, elasticity, and observability without demanding custom effort from the product team.
This is the direction high-velocity engineering is heading: modular infrastructure pieces that are composable and deeply battle-tested. Not all systems need to be cutting-edge. However, the ones handling critical paths, such as state, compute, and messaging, must be predictable, reliable, and invisible.
References:
How we built a general-purpose key-value store for Facebook with ZippyDB
Asynchronous computing @Facebook: Driving efficiency and developer productivity at Facebook scale
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