标签：#service

With its music focus, no-AI content policy, and larger artist royalties, the hi-res streaming service is scooping up all sorts of switchers.

The partnership will see TCS creating a business unit focused on deploying Anthropic's AI models to its customers.

ServiceNow is used by thousands of enterprises to automate their internal processes, but says several customers had data accessed because of a security bug.

When you expose inventory or checkout endpoints to public-facing front-ends or third-party webhooks, safeguarding those APIs from brute-force scripts, scraping bots, and inventory hoarding algorithms becomes a critical requirement. Without defensive rate limiting, a single coordinated script can easily overwhelm your database connections. The Problem with Simple Counter Resets A common mistake when setting up basic API protection is using a rigid "Fixed Window" counter (e.g., allowing 100 requests per minute, resetting exactly at the turn of the clock). This creates a massive flaw where a developer can flood your server with 100 requests at 11:59:59 and another 100 requests at 12:00:01, effectively doubling your acceptable burst traffic and causing severe performance dips. To handle uneven burst traffic safely without crashing your database, the standard approach is implementing a token bucket algorithm. The Token Bucket Pattern The token bucket algorithm maintains a centralized bucket that holds a maximum capacity of tokens. Tokens are added back to the bucket at a constant, predictable rate over time. Each incoming API request consumes exactly one token. If the bucket is completely empty, the request is instantly rejected with a 429 Too Many Requests status code, protecting your core server threads. javascript // Quick Redis-based token bucket rate limiter concept async function isRateLimited(userId) { const key = `rate:${userId}`; const now = Date.now(); // Use a Redis multi-exec transaction to atomically check and update tokens const [tokens, lastRefill] = await redis.hmget(key, 'tokens', 'lastRefill'); // Calculate token replenishment based on time elapsed... // Return true if tokens <= 0, otherwise decrement tokens and update timestamp }

At some point, a monolith starts working against you. In my case, Finovara was a single Spring Boot application handling everything (authentication, transactions, limits, piggy banks, notifications, activity logs, currency conversion) The bigger it got, the harder it was to change anything without worrying about something else breaking. So I broke it apart. This post is about the first three pieces I extracted: the API Gateway , the activity-log-backend , and a shared module called contracts-backend . The Old Structure Everything lived in one Spring Boot app. The activity log — which tracks everything a user does in the app (expenses added, limits changed, logins, account changes) — was tangled up with the core business logic. Adding a new type of activity meant touching the same codebase responsible for transactions, security, and everything else. The New Structure finovara-backend/ ├── api-gateway/ ├── activity-log-backend/ ├── contracts-backend/ └── core-backend/ Four modules (there will be more). Each with a clear responsibility. API Gateway The gateway is the single entry point for every request coming from the frontend. It runs on port 8888 with SSL enabled and uses Spring Cloud Gateway (WebFlux-based). Routing is simple and declarative: routes : - id : activity-log-backend uri : ${ACTIVITY_LOG_URL} predicates : - Path=/api/account-activity/**,/api/archive-activities/** - id : notification-backend uri : ${NOTIFICATION_BACKEND_URL} predicates : - Path=/api/notification-settings/** - id : core-backend uri : ${CORE_BACKEND_URL} predicates : - Path=/** Activity log routes go to activity-log-backend . Notification routes go to notification-backend . Everything else falls through to core-backend . The gateway also handles CORS centrally — https://localhost:5173 is the only allowed origin, with credentials support. No individual service needs to worry about CORS anymore. One thing worth noting: the gateway uses use-insecure-trust-manager: true for the HTTP client. Th

At some point, a monolith starts working against you. In my case, Finovara was a single Spring Boot application handling everything (authentication, transactions, limits, piggy banks, notifications, activity logs, currency conversion) The bigger it got, the harder it was to change anything without worrying about something else breaking. So I broke it apart. This post is about the first three pieces I extracted: the API Gateway , the activity-log-backend , and a shared module called contracts-backend . The Old Structure Everything lived in one Spring Boot app. The activity log — which tracks everything a user does in the app (expenses added, limits changed, logins, account changes) — was tangled up with the core business logic. Adding a new type of activity meant touching the same codebase responsible for transactions, security, and everything else. The New Structure finovara-backend/ ├── api-gateway/ ├── activity-log-backend/ ├── contracts-backend/ └── core-backend/ Four modules (there will be more). Each with a clear responsibility. API Gateway The gateway is the single entry point for every request coming from the frontend. It runs on port 8888 with SSL enabled and uses Spring Cloud Gateway (WebFlux-based). Routing is simple and declarative: routes : - id : activity-log-backend uri : ${ACTIVITY_LOG_URL} predicates : - Path=/api/account-activity/**,/api/archive-activities/** - id : notification-backend uri : ${NOTIFICATION_BACKEND_URL} predicates : - Path=/api/notification-settings/** - id : core-backend uri : ${CORE_BACKEND_URL} predicates : - Path=/** Activity log routes go to activity-log-backend . Notification routes go to notification-backend . Everything else falls through to core-backend . The gateway also handles CORS centrally — https://localhost:5173 is the only allowed origin, with credentials support. No individual service needs to worry about CORS anymore. One thing worth noting: the gateway uses use-insecure-trust-manager: true for the HTTP client. Th

Netflix has shared details about Service Topology. This internal system creates and updates a live dependency graph for thousands of microservices. It helps engineers see how services connect and resolve issues more quickly. The system merges three separate data sources into a single, queryable graph. It updates almost in real-time as traffic patterns shift. By Claudio Masolo

EveryPlate is an actual budget meal kit whose plates taste delicious. Options and ingredients are fewer, but simplicity can also be a virtue.

AWS disclosed that Resilient Network Graphs, a flat network architecture based on quasi-random graph theory, is now the default for most new data center builds. The design replaces fat-tree hierarchies with direct ToR-to-ToR mesh connections using passive optical ShuffleBoxes, cutting routers by 69%, boosting throughput by 33%, and reducing network power consumption by 40%. By Steef-Jan Wiggers

Plex has come a long way from being just a personal media server. Over the past few years, it has transformed into a streaming hub, today featuring ad-supported content and movie rental options. Now, the company is setting its sights on competing with social networking platforms like Reddit and Letterboxd: on Wednesday, Plex unveiled several […]

With inflation and gas prices rising, I’m trying to save money wherever I can. I tested Tello’s budget cell phone plan, and for me, it turns out prepaid can be just as good.