CN113626151B - Container cloud log collection resource control method and system - Google Patents
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Abstract
The invention belongs to the field of cloud computing, and provides a container cloud log collection resource control method and system. The method comprises the steps of configuring the scanning frequency, the log priority and the flow control threshold of a log container; initializing limited resources of a log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by a log container engine; scanning the log files within the log container based on the configured scanning frequency; the method comprises the steps of monitoring the instantaneous flow of a network outlet of a log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the number of bytes per packet and the sending speed according to the sending factor.
Description
Technical Field
The invention belongs to the field of cloud computing, and particularly relates to a container cloud log collection resource control method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the popularization of cloud computing, in order to quickly solve various problems in applications, log analysis becomes an indispensable main means, and log collection, storage and retrieval become key technologies. The traditional log processing mode is that the log is written on a local disk, is only used for checking on-line problems, is rarely used for data analysis, and is logged on a machine to be checked by a command line when required. The containers and the application logs deployed therein, particularly those that have used the container orchestration system, the container of which machine the log is on, and the container application on which the business occurs when multiple container instances are applied, are all uncertain, which undoubtedly increases the difficulty of log analysis.
For this purpose, the industry developed related solutions and techniques based on the de facto standard open-source project Kubernetes (hereinafter K8S) of the container cloud. Currently there are two output forms for container journals, stdout and stderr standard output and journaling file records. Kubernetes does no container log collection work, but provides three related schemes: the first is daemon (daemon) mode, the second is Sidecar (Sidecar) mode, the third is a mixed mode, the second mode is adopted, application logs are copied to a node directory, and then collected by the first mode, and the situation that the node stores two logs can occur.
In the second Sidecar (Sidecar) approach: and running a sidecar container in the Pod, wherein the sidecar container is used for collecting logs generated by the POD main container, and the sidecar is started in preference to the main container, is suitable for collecting application logs, does not invade the container in which the application is located, but invades the Pod in which the application is located. Third native approach: direct intrusion into the application container is required using kubecl logs to view locally maintained logs directly, or by the log driver of the container engine redirecting the logs into the system of files, syslog, fluentd, etc. Where Pod is made up of one or more containers (e.g., docker containers) and has the ability to share storage/network/UTS/PIDs, as well as the specifications of the operating container. And in Kubernetes Pod is the smallest atomic unit that can be scheduled.
The inventor finds that although the second Sidecar mode is an industry standard scheme, if a plurality of Sidecar containers work at full load concurrently, the problem of overlarge resource consumption occurs, node resources are seriously occupied, the service of a main container is influenced, and even the serious consequence of container breakdown is caused.
Disclosure of Invention
In order to solve the technical problem that collection resources of application logs are consumed greatly in a container cloud side vehicle mode in the background art, the invention provides a container cloud log collection resource control method and system, which can fully reduce consumption of a log function on machine resources and give consideration to timeliness of log collection.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a first aspect of the present invention provides a container cloud log collection resource control method, including:
configuring the scanning frequency, the log priority and the flow control threshold of a log container;
initializing limited resources of a log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by a log container engine;
scanning the log files within the log container based on the configured scanning frequency;
the method comprises the steps of monitoring the instantaneous flow of a network outlet of a log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the number of bytes per packet and the sending speed according to the sending factor.
Further, three configuration items of the scanning frequency of the log container, the log priority and the flow control threshold are stored in the etcd service.
Further, the configuration of the scan frequency configuration item of the log container is in seconds.
Further, when the scan frequency configuration item of the log container is configured to be quasi-real time, frequency control is not performed.
Further, when the log priority configuration item of the log container is configured to be a priority not set, priority control is not participated.
Further, the configuration unit MB/sec of the flow control threshold configuration item of the log container.
Further, a token bucket algorithm is employed to control log output flow control when scanning log files within a log container based on a configured scanning frequency.
A second aspect of the present invention provides a container cloud log collection resource control system comprising:
the parameter configuration module is used for configuring the scanning frequency, the log priority and the flow control threshold value of the log container;
a priority control module for initializing defined resources of the log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by the log container engine;
a log scanning module for scanning log files within the log container based on the configured scanning frequency;
and the flow control module is used for monitoring the instantaneous flow of the network outlet of the log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the byte number and the sending speed of each sent packet according to the sending factor.
A third aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in a container cloud log collection resource control method as described above.
A fourth aspect of the invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in a container cloud log collection resource control method as described above when the program is executed.
Compared with the prior art, the invention has the beneficial effects that:
the method effectively allocates the resource consumption peak value when the log output quantity of the multi-application container is large to the subsequent time window, thereby not only integrally improving the node operation efficiency, but also achieving the purpose of protecting the continuous operation of the main container application.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of a side truck in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of container cloud log collection resource control logic of an embodiment of the present invention;
fig. 3 is a token bucket algorithm of an embodiment of the invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
As known from the background art, the side car mode of log collection is, as shown in fig. 1, a scheme of directly reading the log file of the application and sending the log file to a remote storage through a side car (sidecar) container. I.e., put the log agent into the Pod where the application is located, rather than on the node. In this way, when the application container is deployed onto k8s, the business container writes the log in a Volume, such as under the/var/logs directory. Because Volume is shared in Pod, the sidecar container (log container) must directly read the log file by sharing the Volume, then forward the log file to the centralized elastic search storage by fluent log component, and then build index, facilitating subsequent retrieval. The advantage of this solution is that it is not invasive to the application container and does not require modification of the application log module. The method is suitable for most container application log scenes, and can flexibly manage the sidecar containers. The scheme is simple to deploy, has strong multi-tenant isolation and is very friendly to a host machine, so that the scheme becomes a main log collection scheme. The disadvantage of the side-by-side approach to log collection is that this approach is not suitable for scenarios where multiple application containers on a node continue to produce a large number of log records. For example, when multiple sidecar containers work concurrently under full load, the problem of excessive resource consumption occurs, node resources (memory and network) are seriously occupied, the service of the main container is affected, and even the whole Pod is towed.
As shown in fig. 2, in order to solve the above-mentioned problem, the present embodiment provides a container cloud log collection resource control method, which specifically includes the following steps:
step 1: the scanning frequency, the log priority and the flow control threshold of the log container are configured.
The design principle of the side car mode is known that the side car container can not generate excessive cpu, memory and network consumption when running, but generate a large amount of resource consumption when the log is sent in full load due to frequent log scanning and log reading. The new scheme uses the design that a log agent exists in each pod, but a new set of control modules is added, and the three key points of log scanning frequency, log reading and flow control and priority of sending are preconfigured, so that the aim of dynamically regulating and controlling the log collection rhythm according to the configuration during operation is expected to be achieved.
In a specific implementation, when the log container is created, three configuration item scanning frequencies, log priorities and flow control thresholds are added, which are respectively indicated as ScanningFrequency, logSendingPriority, logFlowControl, and the three configuration items are stored in the etcd service.
The etcd is a distributed system for storing key-value, which is distributed and reliable, and is used for storing key data in the distributed system; it is not only used for storage, but also provides configuration sharing and service discovery; based on Go language.
Scanning frequency: the configuration of the scan frequency configuration item of the log container is in seconds. Such as 10s, every 10 s.
When the scanning frequency configuration item of the log container is configured to be quasi-real-time, frequency control is not performed.
LogSendingPriority：
For example: the log priority of the log container is 0-10, with 1 being highest and 10 being lowest. When the log priority configuration item of the log container is configured to be not set with priority, priority control is not participated.
It should be noted that, a person skilled in the art may specifically set the log priority according to the actual situation.
Log flowcontrol: configuration units MB/sec for the flow control threshold configuration items of the log container. If 30 MB/s is configured, no current limit is performed below this value, and 0 is configured to be no flow control.
Step 2: defined resources of the log container are initialized according to the configured log priority, and the upper limit of the resources when the log container runs is controlled by the log container engine.
Step 3: the log files within the log container are scanned based on the configured scanning frequency.
In implementations, a token bucket algorithm is employed to control log output flow control when scanning log files within a log container based on a configured scanning frequency.
As shown in fig. 3, token Bucket algorithm (Token Bucket):
over time, the system will add Token to the bucket at constant 1/QPS intervals (10 ms if qps=100) and will not add if the bucket is full. The new requests are made to temporarily remove one Token each and block or deny service if no Token is available. Another benefit of token buckets is the speed at which they can be easily changed. Once the rate needs to be increased, the rate of tokens placed in the bucket is increased as needed. A number of tokens is typically added to the bucket at regular time (e.g., 100 ms), and some variant algorithms calculate the number of tokens that should be added in real time.
Step 4: the method comprises the steps of monitoring the instantaneous flow of a network outlet of a log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the number of bytes per packet and the sending speed according to the sending factor.
In order to adjust the fine control of the collection of fluent d in the log container, the above steps are implemented in the collection plug-in of fluent d.
According to the method, the consumption of collection resources of the container cloud logs is reduced, the problem that the consumption of collection resources of the application logs is large in a container cloud side vehicle mode is solved, the consumption of a log function on machine resources is fully reduced, and timeliness of log collection is considered.
The embodiment mainly relates to a set of resource control mechanism added during log acquisition in a side car mode, and three key points of flow control and priority of log reading and sending are controlled through log scanning frequency; the embodiment fully utilizes the original resource isolation and limitation of the container cloud, supports the bottom technologies such as container flow monitoring, container timer (Job) and the like, and most simply realizes a complete set of resource control mechanism.
Example two
The embodiment provides a container cloud log collection resource control system, which specifically comprises the following modules:
the parameter configuration module is used for configuring the scanning frequency, the log priority and the flow control threshold value of the log container;
a priority control module for initializing defined resources of the log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by the log container engine;
a log scanning module for scanning log files within the log container based on the configured scanning frequency;
and the flow control module is used for monitoring the instantaneous flow of the network outlet of the log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the byte number and the sending speed of each sent packet according to the sending factor.
Here, each module of the present embodiment corresponds to each step in the first embodiment, and the implementation process is the same, which is not described here.
Example III
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in a container cloud log collection resource control method as described above.
Example IV
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps in the container cloud log collection resource control method when executing the program.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A container cloud log collection resource control method, comprising:
configuring the scanning frequency, the log priority and the flow control threshold of a log container;
initializing limited resources of a log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by a log container engine;
scanning the log files within the log container based on the configured scanning frequency;
a token bucket algorithm is adopted to control log output flow control when the log files in the log container are scanned based on the configured scanning frequency;
monitoring the instantaneous flow of the network outlet of the log container, and comparing the instantaneous flow with a flow control threshold in real time to adjust the transmission factor of the log container, and regulating and controlling the byte number and the transmission speed of each transmitted packet according to the transmission factor;
the scan frequency, log priority and flow control threshold of the configuration log container are specifically as follows: a log agent design exists in each pod, but a new control module is added, and the three key points of log scanning frequency, log reading and flow control and priority of sending are preconfigured, so that the aim of dynamically regulating and controlling the log collection rhythm according to configuration in running is expected to be achieved;
when a log container is created, three configuration item scanning frequencies, log priorities and flow control thresholds are added and are respectively indicated as ScanningFrequency, logSendingPriority, logFlowControl, and the three configuration items are stored in etcd service;
scanning frequency: when the scanning frequency configuration item of the log container is configured to be quasi-real-time, frequency control is not performed;
log sendingpriority: when the configuration 0 of the log priority configuration item of the log container is not set with priority, the log priority configuration item does not participate in priority control;
log flowcontrol: the flow control threshold configuration item of the log container is configured 0 to be not subject to flow control.
2. The container cloud log collection resource control method of claim 1, wherein the configuration of the scan frequency configuration item of the log container is in seconds.
3. The container cloud log collection resource control method of claim 1, wherein the configuration units MB/sec of the flow control threshold configuration items of the log container.
4. A container cloud log collection resource control system based on the container cloud log collection resource control method according to any one of claims 1 to 3, comprising:
the parameter configuration module is used for configuring the scanning frequency, the log priority and the flow control threshold value of the log container;
a priority control module for initializing defined resources of the log container according to the configured log priority, and controlling the upper limit of the resources when the log container runs by the log container engine;
a log scanning module for scanning log files within the log container based on the configured scanning frequency;
a token bucket algorithm is adopted to control log output flow control when the log files in the log container are scanned based on the configured scanning frequency;
and the flow control module is used for monitoring the instantaneous flow of the network outlet of the log container, comparing the instantaneous flow with a flow control threshold in real time to adjust the sending factor of the log container, and regulating the byte number and the sending speed of each sent packet according to the sending factor.
5. A computer readable storage medium having stored thereon a computer program, characterized in that the program when executed by a processor implements the steps in the container cloud log collection resource control method of any of claims 1-3.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps in the container cloud log collection resource control method of any of claims 1-3 when the program is executed by the processor.
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