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I’m curious to see some of the receivers who will be used in Fantasy lineups in Week 7, especially in deeper formats. While CeeDee Lamb (ankle) and Mike Evans (hamstring) might return to action after extended absences — and Rashee Rice is back now that his six-game suspension is over — we’re still dealing with several ailments at the position.
The new injuries for Week 7 include Puka Nacua (ankle), Garrett Wilson (knee), Marvin harrison Jr. (concussion), Emeka Egbuka (hamstring), D.J. Moore (groin),Josh Downs (concussion) and Calvin Ridley (hamstring). And we’re still monitoring other injuries to players who have been out recently,including Terry McLaurin (quadriceps),Quentin Johnston (hamstring),Ricky Pearsall (knee) and Jauan Jennings (ribs).
You need to keep an eye on the injury report all week, and we’ll have you covered on CBS Sports. And, depending on who is out, we could see guys like elic Ayomanor, Sterling Shepard, Zay Jones, Jordan whittington and Josh Reynolds, among others, playing prominent roles for Fantasy managers in Week 7.
Those are desperation plays, but one or two of them could decide your matchup for this week. And we’ll tell you if any of those guys are start options below.
We’ll also get into the other players to use at quarterback, running back and tight end, and there are a lot of great matchups in Week 7. So let’s get started to make sure your lineups are right for this scoring period.
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Running Backs: Start ’em & Sit ‘Em
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START ‘EM & SIT ‘EM
Wide Receivers
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START ‘EM & SIT ‘EM
Tight End
START ‘EM & SIT ‘EM
KICKERS
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The Rise of Serverless Computing
Serverless computing represents a notable shift in cloud computing, allowing developers to build and run applications without managing servers. This model focuses on executing code in response to events, abstracting away the underlying infrastructure. While not truly “serverless” – servers are still involved – developers are freed from the operational burdens of server provisioning, scaling, and maintainance.
Key Benefits of Serverless Architecture
- Reduced Operational costs: Pay only for the compute time consumed,eliminating costs associated with idle servers.
- Increased scalability: Serverless platforms automatically scale to handle fluctuating workloads.
- Faster Time to Market: Developers can focus on writing code rather than managing infrastructure, accelerating progress cycles.
- Simplified Development: The abstraction of server management simplifies the development process.
- Improved fault Tolerance: Serverless architectures are inherently fault-tolerant, as the platform handles infrastructure failures.
How Serverless Works
Serverless computing typically utilizes Function-as-a-Service (FaaS). Developers write individual functions triggered by events such as HTTP requests, database updates, or scheduled jobs. These functions are deployed to a serverless platform (like AWS Lambda, Google Cloud Functions, or Azure Functions) which automatically manages the execution environment.
Popular Serverless platforms
- AWS Lambda: Amazon’s leading FaaS offering, known for its scalability and integration with other AWS services.
- Google Cloud Functions: Google’s serverless execution environment, offering tight integration with Google Cloud Platform.
- Azure Functions: Microsoft’s serverless compute service,part of the Azure ecosystem.
- Cloudflare Workers: A serverless platform focused on edge computing, delivering low-latency performance.
use Cases for Serverless Computing
Serverless is well-suited for a variety of applications, including:
- Web Applications: Building dynamic websites and APIs.
- Mobile Backends: Providing server-side logic for mobile applications.
- Data Processing: Performing real-time data transformations and analysis.
- Event-Driven Automation: Automating tasks in response to events.
- Chatbots: Developing conversational interfaces.
Challenges of Serverless Computing
Despite its benefits, serverless computing also presents some challenges:
- Cold Starts: The initial invocation of a function may experience latency due to the platform provisioning resources.
- Debugging and Monitoring: Debugging distributed serverless applications can be complex.
- Vendor Lock-in: Dependencies on specific serverless platforms can create vendor lock-in.
- Stateless Nature: functions are typically stateless, requiring external storage for persistent data.
- Complexity with Long-Running Tasks: Serverless functions often have execution time limits.
The Future of serverless
Serverless computing is rapidly evolving. Expect to see continued innovation in areas such as improved cold start times, enhanced debugging tools, and greater portability across platforms. As the technology matures, serverless is poised to become an increasingly dominant paradigm in cloud computing.