An official website of the United States government
Serverless platforms offer on-demand computation and represent a significant shift from previous platforms that typically required resources to be pre-allocated (e.g., virtual machines). As serverless platforms have evolved, they have become suitable for a much wider range of applications than their original use cases. However, storage access remains a pain point that holds serverless back from becoming a completely generic computation platform. Existing storage for serverless typically uses an object interface. Although object APIs are simple to use, they lack the richness, versatility, and performance of file based APIs. Additionally, there is a large body of existing applications that relies on file-based interfaces. The lack of file based storage options prevents these applications from being ported to serverless environments. In this paper, we present F3, a file system that offers features to improve file access in serverless platforms: (1) efficient handling of ephemeral data, by placing ephemeral and non-ephemeral data on storage that exists at a different points along the durability-performance tradeoff continuum, (2) locality-aware data scheduling, and (3) efficient reading while writing. We modified OpenWhisk to support attaching file-based storage and to leverage F3's features using hints. Our prototype evaluation of F3 shows improved performance of up to 1.5--6.5x compared to existing storage systems.
more »
« less
Disaggregated GPU Acceleration for Serverless Applications
Serverless platforms have been attracting applications from traditional platforms because infrastructure management responsibilities are shifted from users to providers. Many applications well-suited to serverless environments could leverage GPU acceleration to enhance their performance. Unfortunately, current serverless platforms do not expose GPUs to serverless applications.
more »
« less
- Award ID(s):
- 2006943
- PAR ID:
- 10439107
- Date Published:
- Journal Name:
- ACM SIGOPS Operating Systems Review
- Volume:
- 57
- Issue:
- 1
- ISSN:
- 0163-5980
- Page Range / eLocation ID:
- 10 to 20
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Serverless computing has freed developers from the burden of managing their own platform and infrastructure, allowing them to rapidly prototype and deploy applications. Despite its surging popularity, however, serverless raises a number of concerning security implications. Among them is the difficulty of investigating intrusions – by decomposing traditional applications into ephemeral re-entrant functions, serverless has enabled attackers to conceal their activities within legitimate workflows, and even prevent root cause analysis by abusing warm container reuse policies to break causal paths. Unfortunately, neither traditional approaches to system auditing nor commercial serverless security products provide the transparency needed to accurately track these novel threats. In this work, we propose ALASTOR, a provenance-based auditing framework that enables precise tracing of suspicious events in serverless applications. ALASTOR records function activity at both system and application layers to capture a holistic picture of each function instances' behavior. It then aggregates provenance from different functions at a central repository within the serverless platform, stitching it together to produce a global data provenance graph of complex function workflows. ALASTOR is both function and language-agnostic, and can easily be integrated into existing serverless platforms with minimal modification. We implement ALASTOR for the OpenFaaS platform and evaluate its performance using the well-established Nordstrom Hello,Retail! application, discovering in the process that ALASTOR imposes manageable overheads (13.74%), in exchange for significantly improved forensic capabilities as compared to commercially-available monitoring tools. To our knowledge, ALASTOR is the first auditing framework specifically designed to satisfy the operational requirements of serverless platforms.more » « less
-
Serverless computing platforms have gained popularity because they allow easy deployment of services in a highly scalable and cost-effective manner. By enabling just-in-time startup of container-based services, these platforms can achieve good multiplexing and automatically respond to traffic growth, making them particularly desirable for edge cloud data centers where resources are scarce. Edge cloud data centers are also gaining attention because of their promise to provide responsive, low-latency shared computing and storage resources. Bringing serverless capabilities to edge cloud data centers must continue to achieve the goals of low latency and reliability. The reliability guarantees provided by serverless computing however are weak, with node failures causing requests to be dropped or executed multiple times. Thus serverless computing only provides a best effort infrastructure, leaving application developers responsible for implementing stronger reliability guarantees at a higher level. Current approaches for providing stronger semantics such as “exactly once” guarantees could be integrated into serverless platforms, but they come at high cost in terms of both latency and resource consumption. As edge cloud services move towards applications such as autonomous vehicle control that require strong guarantees for both reliability and performance, these approaches may no longer be sufficient. In this paper we evaluate the latency, throughput, and resource costs of providing different reliability guarantees, with a focus on these emerging edge cloud platforms and applications.more » « less
-
Serverless computing platforms have gained popularity because they allow easy deployment of services in a highly scalable and cost-effective manner. By enabling just-in-time startup of container-based services, these platforms can achieve good multiplexing and automatically respond to traffic growth, making them particularly desirable for edge cloud data centers where resources are scarce. Edge cloud data centers are also gaining attention because of their promise to provide responsive, low-latency shared computing and storage resources. Bringing serverless capabilities to edge cloud data centers must continue to achieve the goals of low latency and reliability. The reliability guarantees provided by serverless computing however are weak, with node failures causing requests to be dropped or executed multiple times. Thus serverless computing only provides a best effort infrastructure, leaving application developers responsible for implementing stronger reliability guarantees at a higher level. Current approaches for providing stronger semantics such as ``exactly once'' guarantees could be integrated into serverless platforms, but they come at high cost in terms of both latency and resource consumption. As edge cloud services move towards applications such as autonomous vehicle control that require strong guarantees for both reliability and performance, these approaches may no longer be sufficient. In this paper we evaluate the latency, throughput, and resource costs of providing different reliability guarantees, with a focus on these emerging edge cloud platforms and applications.more » « less
-
While serverless platforms substantially simplify the provisioning, configuration, and management of cloud applications, implementing correct services on top of these platforms can present significant challenges to programmers. For example, serverless infrastructures introduce a host of failure modes that are not present in traditional deployments. Individual serverless instances can fail while others continue to make progress, correct but slow instances can be killed by the cloud provider as part of resource management, and providers will often respond to such failures by re-executing requests. For functions with side-effects, these scenarios can create behaviors that are not observable in serverful deployments. In this paper, we propose mu2sls, a framework for implementing microservice applications on serverless using standard Python code with two extra primitives: transactions and asynchronous calls. Our framework orchestrates user-written services to address several challenges, such as failures and re-executions, and provides formal guarantees that the generated serverless implementations are correct. To that end, we present a novel service specification abstraction and formalization of serverless implementations that facilitate reasoning about the correctness of a given application’s serverless implementation. This formalization forms the basis of the mu2sls prototype, which we then use to develop a few real-world microservice applications and show that the performance of the generated serverless implementations achieves significant scalability (3-5× the throughput of a sequential implementation) while providing correctness guarantees in the context of faults, re-execution, and concurrency.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3606557.3606560
